Power, Innovation, and Language Creativity in an Online Community of Practice
A thesis submitted to The University of Manchester for the degree of Doctor of Philosophy in the Faculty of Humanities
2020
Lisa Donlan
School of Arts, Languages and Cultures
Contents
List of figures ...... 6 List of tables...... 9 Abstract ...... 10 Declaration...... 11 Copyright statement ...... 12 Acknowledgements ...... 13 1 Chapter 1: Introduction ...... 14 Rationale for research...... 14 Research questions ...... 15 Contributions ...... 17 Structure of the thesis ...... 18 2 Chapter 2: The Community of Practice framework ...... 20 Introduction ...... 20 The Community of Practice framework ...... 20 Online Communities of Practice ...... 22 Communities of Practice in linguistics...... 23 Communities of Practice and language creativity ...... 26 Communities of Practice and power ...... 29 Issues with linguistic definitions of power in the Community of Practice framework ...... 29 The Community of Practice framework and the handling of power...... 30 The Community of Practice framework, power, and the weak-tie theory of language change ...... 31 The Community of Practice framework, power, status, and hierarchy ...... 34 The Community of Practice framework, power, and content moderation...... 39 Conclusion ...... 42 3 Chapter 3: Methodology ...... 45 Introduction ...... 45 Data selection ...... 45 Data collection...... 46 Data analysis ...... 47 Linguistic forms for analysis ...... 47 Defining power, status, and hierarchy ...... 49 Measuring status ...... 50 2
Ethnography...... 56 The weak-tie theory of language change: innovators ...... 57 The weak-tie theory of language change: early adopters ...... 58 Power, control, and linguistic content moderation ...... 62 Limitations ...... 62 Ethics ...... 64 Data presentation ...... 65 Conclusion ...... 65 4 Chapter 4: The Popheads Community of Practice ...... 66 Introduction ...... 66 Reddit ...... 66 Overview of Popheads ...... 69 Size of the Popheads community ...... 70 Demographic overview ...... 72 The moderators ...... 79 Language creativity ...... 81 Popheads as a Community of Practice ...... 83 5 Chapter 5: Case study 1 – delete it fat ...... 89 Introduction ...... 89 Community usage ...... 89 The weak-tie theory of language change...... 94 The innovator ...... 94 The early adopters ...... 98 Conclusion ...... 110 Status, hierarchy, power, and the delete it fat LCM policy ...... 111 Advocation for the LCM policy ...... 111 Implementation of the LCM policy ...... 118 Effectiveness of the LCM policy ...... 123 Conclusion ...... 135 6 Chapter 6: Case study 2 – buy x on iTunes...... 137 Introduction ...... 137 Community usage ...... 137 The weak-tie theory of language change...... 143 The innovator ...... 143 The early adopters ...... 145
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Conclusion ...... 155 Status, hierarchy, power, and the buy x on iTunes LCM policy ...... 156 Advocation for the LCM policy ...... 156 Implementation of the LCM policy ...... 158 Effectiveness of the LCM policy ...... 160 Conclusion ...... 168 7 Chapter 7: Case study 3 – wig ...... 170 Introduction ...... 170 Community usage ...... 170 The weak-tie theory of language change...... 174 The innovator ...... 174 The early adopters ...... 176 Conclusion ...... 186 Status, hierarchy, power, and the wig LCM policy ...... 187 Advocation for the LCM policy ...... 187 Implementation of the LCM policy ...... 197 Effectiveness of the LCM policy ...... 198 Conclusion ...... 203 8 Chapter 8: Case study 4 – tea ...... 205 Introduction ...... 205 Community usage ...... 205 The weak-tie theory of language change...... 209 The innovator ...... 209 The early adopters ...... 212 Conclusion ...... 222 9 Chapter 9: Discussion ...... 224 The community of practice framework and the weak-tie theory of language change...... 224 RQ1.1 Does the weak-tie theory of language change's prediction about linguistic innovators hold in an online CofP ...... 225 RQ1.2 Does the weak-tie theory of language change's prediction about early adopters hold in an online CofP? ...... 230 RQ1.3 Which status markers are statistically significant predictors of early adopter status? ...... 232 Power, status, and the control of linguistic resources in an online Community of Practice...... 235
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10 Chapter 10: Conclusion...... 243 Introduction ...... 243 Contributions ...... 243 Limitations and future research directions ...... 244 Concluding remarks ...... 246 Reference List ...... 247
Word count: 77,638
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List of figures
Figure 4.1: Graph showing the number of subscribers, active members, and full members of the Popheads community throughout the data collection period...... 71 Figure 4.2: Graph showing the number of active members and full members of the Popheads community throughout the data collection period...... 71 Figure 4.3: Self-reported gender of Popheads users...... 74 Figure 4.4: Self-reported age of Popheads users in February 2016...... 75 Figure 4.5: Self-reported age of Popheads users in April 2017 and April 2018...... 75 Figure 4.6: Self-reported sexuality of Popheads users...... 76 Figure 4.7: Self-reported ethnicity of Popheads users...... 77 Figure 4.8: Percentage of Popheads users from North America...... 78 Figure 4.9: Percentage of Popheads users with English as their first language...... 79 Figure 5.1: Cumulative number of users of delete it fat...... 99 Figure 5.2: Percentage of early adopters of delete it fat who scored above, at, or below the community median for the quantitative status markers...... 100 Figure 5.3: Correlation matrix for the early adopter/non-adopter delete it fat dataset...... 104 Figure 5.4: The proportion of variance accounted for by the principal components identified in the early adopter/non-adopter delete it fat dataset...... 105 Figure 5.5: Loadings for PC1 in the early adopter/non-adopter delete it fat dataset...... 106 Figure 5.6: Loadings for PC2 in the early adopter/non-adopter delete it fat dataset...... 107 Figure 5.7: Plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter delete it fat dataset...... 108 Figure 5.8: Simplified plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter delete it fat dataset...... 108 Figure 5.9: Raw and normalised frequency of delete it fat in the Popheads corpus...... 114 Figure 5.10: Raw and normalised frequency of delete it fat in the Popheads corpus...... 123 Figure 5.11: Number of posts removed by the Popheads moderators...... 125 Figure 5.12: Monthly usage of synonym variants of delete it fat vs all other forms of the expression...... 126 Figure 5.13: Image uploaded to Popheads by
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Figure 6.4: The proportion of variance accounted for by the principal components identified in the early adopter/non-adopter buy x on iTunes dataset...... 151 Figure 6.5: Loadings for PC1 in the early adopter/non-adopter buy x on iTunes dataset...... 151 Figure 6.6: Loadings for PC2 in the early adopter/non-adopter buy x on iTunes dataset...... 152 Figure 6.7: Plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter buy x on iTunes dataset...... 153 Figure 6.8: Simplified plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter buy x on iTunes dataset...... 153 Figure 6.9: Raw and normalised frequency of buy x on iTunes in the Popheads corpus...... 160 Figure 6.10: The number of status markers on which the violators of the buy x on iTunes LCM policy score higher than the community median...... 166 Figure 6.11: The status markers on which violators of the buy x on iTunes LCM policy score higher than the community median...... 167 Figure 7.1: Cumulative number of users of wig...... 176 Figure 7.2: Percentage of early adopters of wig who scored above, at, or below the community median for the quantitative status markers...... 177 Figure 7.3: Correlation matrix for the early adopter/non-adopter wig dataset...... 181 Figure 7.4: The proportion of variance accounted for by the principal components identified in the early adopter/non-adopter wig dataset...... 182 Figure 7.5: Loadings for PC1 in the early adopter/non-adopter wig dataset...... 182 Figure 7.6: Loadings for PC2 in the early adopter/non-adopter wig dataset...... 183 Figure 7.7: Plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter wig dataset...... 184 Figure 7.8: Simplified plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter wig dataset...... 184 Figure 7.9: Raw and normalised frequency of wig in the Popheads corpus...... 199 Figure 7.10: Daily normalised frequency (per million words) of wig in the Popheads corpus (1st January 2018 - 31st May 2018)...... 200 Figure 7.11: The number of status markers on which the violators of the wig LCM policy score higher than the community median...... 202 Figure 7.12: The status markers on which violators of the wig LCM policy score higher than the community median...... 203 Figure 8.1: Cumulative number of users of tea...... 213 Figure 8.2: Percentage of early adopters of tea who scored above, at, or below the community median for the quantitative status markers...... 214 Figure 8.3: Correlation matrix for the early adopter/non-adopter tea dataset...... 217 Figure 8.4: The proportion of variance accounted for by the principal components identified in the early adopter/non-adopter tea dataset...... 218 Figure 8.5: Loadings for PC1 in the early adopter/non-adopter tea dataset...... 218 Figure 8.6: Loadings for PC2 in the early adopter/non-adopter tea dataset...... 219 Figure 8.7: Plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter tea dataset...... 220
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Figure 8.8: Simplified plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter tea dataset...... 220
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List of tables
Table 5.1: Status markers for
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Abstract This research utilises a mixed-methods approach and a near-complete corpus of all posts made to Popheads, a Reddit-based online music-orientated Community of Practice (CofP), to analyse two key unresolved topics in the intersection between CofP theory and sociolinguistics. The first topic centres on the applicability of the weak-tie theory of language change (Milroy & Milroy 1985) to an online CofP. The principles of this theory have been found to hold in studies of offline CofPs (Bucholtz 1999; Eckert 1988; Eckert 2000; Mendoza-Denton 2008; Moore 2010), yet the only study to explore the theory in an online CofP was grounded in an ungeneralisable linguistic context (Stewart et al. 2017). The first research question subsequently asks if the weak tie theory's prediction that the innovators of linguistic forms will be peripheral members holds in an online CofP. On the contrary, three of the four forms studied were innovated by non-peripheral members who scored highly across multiple markers of status. This departure from previous findings may be related to the more positive attitudes towards linguistic creativity in online environments. The second research question asks if the weak tie theory's prediction that the early adopters of linguistic forms would be high-status members holds in an online CofP. This research concluded that while there were four status markers that the majority of early adopters scored higher than the community median on, there were five others that did not appear to be linked to early adoption. Therefore, the monodimensional concept of being 'high-status' was shown to be an overly simplistic way of conceptualising the multidimensional concept of status. The most satisfactory answer to this research question is that members who are early adopters tend to score highly across four markers of status ('comments contributed', 'replies received', 'submissions contributed', and 'months active'). The third research question uses principal component analysis and logistic regression analysis to determine which status markers are statistically significant predictors of early adopter status. All four case studies showed that 'commenting behaviour' was a statistically significant predictor, with early adopters tending to be highly prolific commenters. Three of the four case studies demonstrated that a measure which approximates if members are on inbound or outbound trajectories in the community was also a statistically significant predictor of early adopter status, with early adopters tending to be dedicated members on inbound trajectories. Finally, two of the four case studies also confirmed an interaction between these two variables: being a prolific commenter and being on an inbound trajectory is a significant predictor of early adopters status. This research concludes that what is important when considering early adopter status is where members sit on multiple hierarchies and their position in the intersection of those hierarchies. Meanwhile, the second unresolved topic explores the relationship between power, status and hierarchy by looking at the stages of linguistic content moderation, in which community-salient linguistic forms were banned from usage in the Popheads community. I conclude that the relationship between power, status and hierarchy is more complex and multidimensional than suggested in much of the current CofP literature (Davies 2005; Kerno 2008; Moore 2006; Wenger 2010). There are multiple hierarchies at work in this CofP and having high status in certain hierarchies seems to correlate with power to control and influence linguistic content moderation policies. For instance, having moderator status gives members the power to implement and enforce content moderation policies, while prolific comment contribution seems to correlate with the power to take back control of the lexicon and violate the linguistic content moderation policies.
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Declaration
I declare that no portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.
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Copyright statement i. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the "Copyright") and s/he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes. ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made. iii. The ownership of certain Copyright, patents, designs, trademarks and other intellectual property (the "Intellectual Property") and any reproductions of copyright works in the thesis, for example graphs and tables ("Reproductions"), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions. iv. Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=24420), in any relevant Thesis restriction declarations deposited in the University Library, The University Library's regulations (see http://www.library.manchester.ac.uk/about/regulations/) and in The University's policy on Presentation of Theses
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Acknowledgements Firstly, I would like to extend my deepest gratitude to my PhD supervisors, Prof. Maj-Britt Mosegaard Hansen and Dr Andrea Nini, and my independent reviewer, Dr Anke Bernau. My supervisors have opened doors to extraordinary opportunities, read hundreds of thousands of words of my writing, and provided me with consistently detailed and constructive feedback. I could not have asked for a better supervisory team, and I am eternally grateful for their support, advice, and encouragement.
I also wish to thank the Economic and Social Research Council (ESRC) and the Arts and Humanities Research Council (AHRC) for granting me a joint 1+3 studentship to undertake this research.
I could not write these acknowledgements without mentioning the two women who inspired my love for the English language and set me on this career path: my sixth form English Language teacher, Gill Shaw, and my undergraduate dissertation supervisor and mentor, Dr Maggie Scott.
I would also like to acknowledge my Linguistics and English Language undergraduate students (and especially the graduating class of 2020), who kept me sane and inspired me with their hard work, passion, and determination.
Parts of this thesis are currently in print for a chapter in an upcoming edited volume, Corpus Approaches to Social Media (Donlan 2020). I would like to thank the editors, Daria Dayter & Sofia Rüdiger, and two anonymous reviewers for their invaluable feedback.
I am also grateful to my brother, Mike Donlan, for always putting a smile on my face, and my dearest friends, Nauraiza Ashraf and Sarah Mahmood, for their unwavering patience, compassion, and belief.
Last, but by no means least, I would like to thank my wonderful mum, the kindest and most loving person in my world. I could not have completed my PhD without her, and this thesis is dedicated to her.
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1 Chapter 1: Introduction
Rationale for research
The Community of Practice (CofP) theory was pioneered by education theorists Jean Lave and Étienne Wenger (1991) to describe how newcomers learn the norms of a community by being allowed to participate incrementally in its practices. CofPs are distinguished from other structures such as social networks or speech communities by their focus and orientation around practices, which are succinctly defined by Eckert (2000: 35) as "share[d] ways of doing things, ways of talking, beliefs, values". Furthermore, as outlined by Wenger (1998: 72–85), for a community to be a CofP, there must be mutual engagement between members as they partake in practices which contribute to a joint enterprise, out of which a shared repertoire (which can encompass words, expressions, in-jokes, narratives, and so on) must emerge. Since its introduction to the linguistic discipline by Eckert and McConnell-Ginet (1992a; 1992b), the framework has proven to be popular, with one of the key advantages being that it brings the social practices and contexts in which language is produced and used to the forefront of study (Eckert & McConnell-Ginet 1992a). Nevertheless, there are several open questions relating to the use of CofP in linguistics, the answers to which may also have interesting and far-reaching consequences for the discipline of sociolinguistics more generally. Firstly, Davies (2005) recommends that the weak-tie theory of language change, which emerged from second-wave sociolinguistic social network analysis research (Milroy & Milroy 1985), should be incorporated into the CofP framework to aid with the conceptualisation of the role of linguistic innovators and early adopters in a CofP. This conceptualisation envisions the innovators of linguistic forms as peripheral members of the community and the early adopters as the community's leaders or central figures. The findings from numerous studies of offline CofPs have provided support for elements of this hypothesis (Bucholtz 1999; Eckert 1988; Eckert 2000; Mendoza-Denton 2008). However, there is only one study of an online CofP which can be related to this hypothesis (Stewart et al. 2017), and the findings are grounded in a highly unusual – and potentially ungeneralisable – linguistic context (as will be discussed in Chapter 2). The scarcity of research on the applicability of the
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weak-tie theory to online CofPs is especially concerning in light of work in the social network tradition which has questioned the applicability of elements of the weak-tie theory to online social networks (Bergs 2006; Huffaker 2010; Kooti et al. 2012). Secondly, one of the most notable controversies within CofP theory that has played out, in part, across the pages of linguistic journals is the relationship between hierarchy, status, and power in the CofP framework. The full debate on this topic will be reviewed in Chapter 2. However, in summary, there are four different viewpoints put forth in the literature about the relationship between hierarchy and power. The first view holds that CofPs are composed of horizontal hierarchies where no individual or subgroup has power over other members of the community (Kerno 2008; Wenger 2010). The second view holds that CofPs are composed of vertical hierarchical structures, and only those at the top of the hierarchy have the power to control and influence the community and its resources (Davies 2005; Silva, Goel & Mousavidin 2009). The third position, advocated for by Moore (2006), contends that although CofPs may have top-down hierarchical structures, any legitimate member of the community can potentially control or influence the community and its resources. The fourth and final position holds that hierarchical structures and power dynamics are more fluid and context-dependent than suggested in the above hypotheses (Mak & Chui 2013; Wilson 2009). This research is centred on exploring these two open areas in the intersection between sociolinguistics and CofP: the applicability of the weak-tie theory of language change to online CofPs and the relationship between power, status, and hierarchy. Power is defined here as the ability to consciously or unconsciously control or influence other people's behaviour in a specific social context, while status is a person's location in the hierarchy (or hierarchies) of the community, which can be approximated by a series of mostly quantifiable measures. Indeed, one of the fundamental assumptions of this research is that power and status (and the relationship between the two) may be more complex and multidimensional than accounted for in much of the literature.
Research questions
The research questions and hypotheses explored in this research are as follows:
RQ1.1 Does the weak-tie theory of language change's prediction about linguistic innovators hold in an online CofP?
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▪ H1.1. Peripheral members will be the innovators of linguistic forms.
RQ1.2 Does the weak-tie theory of language change's prediction about early adopters hold in an online CofP?
▪ H1.2. Members with high-status will be the early adopters of linguistic forms.
RQ1.3 Which status markers (if any) are statistically significant predictors of early adopter status?
▪ H1.3 All status markers will be statistically significant predictors of early adopter status.
RQ2: Who has the power to control or influence linguistic resources in the Popheads CofP?
▪ H2.1 CofPs are composed of horizontal power structures (Kerno 2008; Wenger 2010). ▪ H2.2 CofPs are composed of vertical hierarchical structures, and those at the top control and influence the community and its resources (Davies 2005; Silva, Goel & Mousavidin 2009). ▪ H2.3 CofPs may have top-down hierarchical structures, but all legitimate members can potentially control/influence the community and its resources (Moore 2006). ▪ H2.4 The conceptualisations of the relationship between power and hierarchy in H2.1 – H2.3 are too simplistic.
In order to explore these research questions, I draw on a corpus of over one million posts collected from Popheads, an online CofP dedicated to pop music which is hosted on the website Reddit. The Popheads corpus represents a near-complete collection of all posts contributed to the CofP between its creation in August 2015 and the end of the data collection period in May 2018. More specifically, to answer the research questions, I performed in-depth qualitative and quantitative case studies of four community-salient innovative linguistic forms which emerged and diffused through the CofP during the data collection period. These forms are delete it fat ('I dislike or disagree with your opinion'), buy x on iTunes [where x is the name of
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a song or album] (a way of avowing fandom to x), wig ('surprised' or 'impressed'), and tea ('gossip'/'truth'). For each of these forms, I study the status profile of the innovator to determine if they can be considered a peripheral member of Popheads at the time they introduced the form, as the weak-tie theory would predict. I also explore the status profiles of the early adopters of these forms to determine if they can be classified as high-status members and to explore if there are any status markers which serve as statistically significant predictors of early adopter status. Meanwhile, RQ2, which is interested in the relationship between power, status, and hierarchy in the CofP, is explored by focusing on the first three case studies (delete it fat, buy x on iTunes, and wig). These forms were all banned from being used in the community by the moderators as part of the community's linguistic content moderation (LCM) policies, during the data collection period. I explore the relationship between power, status, and hierarchy by looking at the intersection between these three concepts and the three stages of LCM in the community: advocation for LCM, its implementation, and its effectiveness.
Contributions
The first key contribution that I make with this work is to explore the extent to which the weak-tie theory of language change can be applied to online CofPs. The findings of this research question have implications for how lexical innovation and diffusion are conceptualised and studied in online communities. Moreover, the findings relating to the weak-tie theory of language change presented in this study are based on a near-complete archive of all interactions in a community for the first thirty-four months of its existence. Thus, every single innovator and early adopter of the forms of interest can be identified and studied. It would be almost impossible to replicate this methodology in an offline context. Therefore, this research could potentially point to novel findings relating to the weak-tie theory of language change which have, thus far, gone undiscovered as a result of the necessary incompleteness of offline datasets. The second key contribution is my exploration of the relationship between power, status, and hierarchy in an online CofP. As will be documented in Chapter 2, the relationship between these concepts is an open question in the CofP literature. By undertaking a systematic and extensive exploration of how these concepts manifest in processes of LCM in the Popheads community, I hope to not only contribute to the understanding of power, status,
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and hierarchy in the CofP framework but to reach conclusions that will inform the sociolinguistic study of power more broadly. Thirdly, in the course of this research, I developed a method, informed by an extensive literature review and ethnographic observations, for measuring status as a multidimensional concept in an online community. Although the method may not be directly generalisable to communities beyond Popheads, it can nevertheless serve as an adaptable blueprint to explore the (potentially) multidimensional nature of status in other online communities. Finally, this is the first study to explore LCM policies which have been implemented and enforced by community members themselves rather than outsiders. The findings relating to the manifestation of power in this interesting linguistic context will likely be of interest to scholars interested in power and linguistic censorship.
Structure of the thesis
Chapter 2, entitled 'The Community of Practice Framework', explores the theoretical framework and issues which underpin this research. Specifically, this chapter introduces the CofP framework, looks at its suitability for studying online communities, and considers how it has been applied in previous linguistic research. The main body of this chapter considers the existing literature which frames the two open themes explored in this research: the role of the weak-tie theory of language change and the relationship between hierarchy, status, and power in CofPs. This chapter then looks at existing CofP work on the relationship between power and LCM, before concluding by recapping the research questions and hypotheses explored in this work. Chapter 3 provides an in-depth overview of the methodology used to explore the research questions, focusing on the processes of data selection, data collection, and data analysis. Under the latter subheading, I also discuss how power, status, and hierarchy are defined and measured in this work and describe the ethnographic component of my analysis. Chapter 3 concludes by considering the methodological limitations of this research and its ethics. Next, Chapter 4 provides a thorough ethnographic-driven analysis of the Popheads community, focusing specifically on its conventions, size, and demographics, before describing how the community meets all of the criteria for being a CofP. This chapter serves
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to place the linguistic analysis in the succeeding chapters into its wider social, cultural, and technological context. Chapters 5 – 8 each explore one of the linguistic forms studied in this research. Each chapter begins with an overview of how the relevant form is defined and used in the Popheads community. Subsequently, the next section considers the extent to which the innovation and diffusion of the form support the weak-tie theory of language change. Finally, I analyse the relationship between status, power, hierarchy, and the endogenous LCM policy relating to the form (this sub-section is omitted from Chapter 8 as tea was not banned during the data collection period). The discussion of the findings will then take place in Chapter 9, where I explore how the hypotheses have been supported or problematised by the qualitative and quantitative analysis in Chapters 5 – 8. Finally, this thesis concludes in Chapter 10 as I outline the contributions that this study makes to the linguistic discipline, explore its limitations, and consider how future research can refine and expand on its findings.
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2 Chapter 2: The Community of Practice framework
Introduction
This chapter explores the key theoretical model in this thesis: the Community of Practice (CofP) framework. In Sections 2.1 – 2.4, I introduce critical components of the framework, look at the suitability of CofP theory for studying online communities, consider how the framework has been applied in linguistic research, and reflect on linguistic creativity in CofPs. Section 2.5 then focuses on the theorisation of power in current CofP literature. To contextualise this topic, I begin by considering the issues surrounding definitions of power in existing linguistic CofP research and outline studies which have questioned the extent to which the framework is useful for modelling community power dynamics. I then turn to focus on existing literature on the two key topics explored in this research: 1) the role of the weak-tie theory of language change in CofPs and 2) the relationship between status, hierarchy, and power in CofPs. I conclude Section 2.5 with an exploration of the relationship between power and LCM in online CofPs. Finally, I summarise the key points – and open questions – explored in the CofP literature, before recapping the hypotheses and research questions explored in the current research.
The Community of Practice framework
The CofP framework was introduced in 1991 by education theorists Jean Lave and Étienne Wenger to account for their ethnographic observations of processes of social learning in the workplace. Specifically, they developed the CofP model, alongside their concept of Legitimate Periphery Participation (LPP), to describe how newcomers to workplace-based CofPs learn the trade by being allowed to participate incrementally in the practices of the community. CofPs are distinguished from other community structures by their focus and orientation around community-specific practices, which are defined as "share[d] ways of
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doing things, ways of talking, beliefs, values" (Eckert 2000: 35). Although, in Lave & Wenger (1991), the concept of the CofP is "left largely as an intuitive notion [...] which requires a more rigorous treatment" (Lave & Wenger 1991: 42), several subsequent publications (Bucholtz 1999; Eckert 2000; Wenger 1998; Wenger, McDermott & Snyder 2002) have transformed the notion into a robust framework. Wenger (1998: 73) outlines three criteria that communities must meet in order to be a CofP. Firstly, there must be mutual engagement between members of the community as they participate in the community's practices. It is possible that a community's methods and modes of engagement may be highly specific to the group and confuse or alienate outsiders (Wegner 1998: 113). Nevertheless, mutual engagement does not necessarily need to be harmonious. Wegner, in fact, notes that CofPs can be characterised by "disagreements, tensions, and conflicts" (1998: 77). Secondly, members of a CofP must engage in a joint enterprise. Meyerhoff and Strycharz (2013: 430) note that the definition of a joint enterprise necessarily involves circularity as "members get together for some purpose and this purpose is defined through the pursuit of it". In other words, the joint enterprise is the purpose behind the practices that members of the CofP mutually engage in, but members will negotiate and (re)define this purpose as they engage in their practices. Finally, as members engage in their joint enterprise, a shared linguistic and non- linguistic repertoire must emerge. Wegner (1998: 83) notes that a shared repertoire may encompass "routines, words, tools, ways of doing things, stories, gestures, symbols, genres, actions, or concepts". Shared repertoires are negotiated continuously, and community members may not agree upon the meaning of all elements. Wegner (1998: 84) writes that meaning is shared "in a dynamic and interactive sense", and he notes that multiple meanings or interpretations only become problematic when they interfere in the practices of the community. In these instances, the subsequent discourses regarding definitions and interpretations that must follow form part of the natural and continuous negotiation of meaning in the CofP. The shared repertoire may be highly specific to the community, to the point where outsiders may not be able to comprehend inside jokes and the references shared by community members (Wenger 1998: 113). On the other hand, the shared repertoire may also encompass elements which are adopted from outside of the community (Wegner 1998: 126). Indeed, CofPs must be understood in their social, historical, and global context: members will likely belong to multiple CofPs simultaneously, and just as practices and
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enterprises may intertwine with those of other CofPs, elements of the shared repertoire may be in use in other communities (Wegner 1998: 116; 126). Wenger (1998: 118) writes that not all members of a CofP participate equally in the community (see also Wenger-Trayner & Wenger-Trayner 2011). It is possible to distinguish different levels of participation, which run from the most engaged full members, who tend to be leaders and experts in the practices of the community, to occasional members, who contribute only when the topic is of particular interest, to peripheral members, who only participate in a limited way, often because they are either newcomers on an inbound trajectory or because they cannot/do not wish to increase their participation (Wenger-Trayner & Wenger-Trayner 2011). The lowest level of participation in a CofP comes from transactional members, who rarely interact with the community. Unlike peripheral members, who also (typically) participate rarely but are granted limited yet legitimate access to the community, transactional members are outsiders, who are generally not considered legitimate members. However, membership in a CofP is not static: members' level of engagement is dynamic (Wenger 1998: 154-155). For instance, members may be on inbound or outbound trajectories, in which they are, respectively, actively increasing or decreasing their participation. Similarly, because meaning and practices in CofPs are continually being negotiated, even the core members must continue on an 'insider' trajectory to ensure they are participating and engaging in the community sufficiently enough to maintain their positions (Wenger 1998: 154).
Online Communities of Practice
Some commentators have expressed doubts that an online community can be a CofP: most of the concern seemingly centres on the 'mutual engagement' criteria for identifying CofPs. Davies (2005), for instance, quotes Wenger's (1998: 74) statement that "talking on the phone, exchanging electronic mail, or being connected by radio can be part of what makes mutual engagement possible". She takes Wenger's qualification through the use of the phrase "part of" to mean that, in Wenger's view, there needs to be some element of face-to-face contact for a CofP to exist (Davies 2005: 561). Similarly, Meyerhoff and Strycharz (2013: 429–430). also conclude from the above quote that Wenger's conceptualisation of a CofP "suggests temporal (if not spatial) simultaneity of contact between members" (2013: 429–430). They
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concede that some online communities (such as chat rooms and those which employ instant messaging services) may allow synchronic communication and thus satisfy what they have interpreted as the requirement of temporal simultaneity. However, they do not address the possibility that an online community which facilitates neither temporal nor spatial simultaneity could be a CofP. Nevertheless, research from a variety of disciplines has documented the existence of both synchronous and asynchronous online communities that meet the criteria for a CofP. Indeed, studies have explored online CofPs consisting of healthcare providers (Roland, Spurr & Cabrera 2017; Seibert 2015; Thoma et al. 2018), educators (Cho 2016), gamers (Lakhmani et al. 2016), and Wikipedia contributors (Bryant, Forte & Bruckman 2005). The framework has perhaps been applied in online environments less often by linguists than by researchers in other disciplines such as education. However, there is nevertheless a growing body of linguistic research which has a) documented the existence of online CofPs and b) applied the framework to aid in the linguistic exploration of CMC (Dayter & Rüdiger 2020; Kavanagh 2017; Nishmura 2003; Silva, Goel & Mousavidin 2009; Stommel 2008; Stommel & Koole 2010; Witten 2014).
Communities of Practice in linguistics
Lave & Wenger (1991: 105), in one of the first publications on the CofP framework, wrote that "learning to become a legitimate participant in a community involves learning how to talk (and be silent) in the manner of full participants". Issues relating to language and discourse, then, have been central to the theory since the outset. The CofP framework, at its heart, is a theory of social learning, and it provides linguists with a framework to account for how members of a community learn "the language norms of the community, the community register, and the linguistic elements of the shared repertoire" (Witten 2014: 12). It is useful to distinguish CofPs from other frameworks used to conceptualise communities in linguistics, such as speech communities and social networks (Bucholtz 1999; Eckert & McConnell-Ginet 1992a; Witten 2014). The speech community framework was popularised in linguistics in the 1960s and 1970s (Labov 1966; Labov 1972a) and continues to be regularly used in contemporary sociolinguistic research (Daleszynska-Slater, Meyerhoff & Walker 2019; Tagliamonte & D’Arcy 2007; Tagliamonte & Roeder 2009; Singer 2018). Bucholtz (1999: 207-210) outlines
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several key differences between the speech community model and the CofP model. Firstly, she argues that speech community analysis is interested primarily in language, while the CofP approach considers language to be no more important than other social practices. A second difference is that the CofP model requires mutual engagement between members, whereas members of a speech community can theoretically be strangers. Thirdly, Bucholtz argues that the speech community framework treats the identities of individuals and the community as static; in contrast, the CofP framework holds that practices, identities, and meaning are always in negotiation. Finally, there is a tendency for the speech community model to focus primarily on central individuals in the community, while the CofP framework is interested all members of the community, including those at the periphery. Another community model often used in sociolinguistic studies is social network analysis (hereafter SNA). SNA postulates that individuals are not isolated entities, and, instead, they exist in networked communities where their relationships to other people can be mapped, visualised, and analysed (Vetter et al. 2011: 208). Implicit in SNA is the notion that information and other resources (both linguistic and non-linguistic) can diffuse through networks via relationships formed between individuals (Garton, Haythornthwaite & Wellman 1997). There are many similarities between SNA and the CofP framework: both are interested in the relationships between members of localised, clearly defined communities and both are interested in all members of the community, regardless of their role or status. However, the two concepts are not synonymous. For instance, in her study of a Scottish pipe band, Clark (2009) determined that some of the social network clusters identified lacked the associated practices or levels of commitment to a joint enterprise which would have qualified them for the label of a CofP. Furthermore, Witten (2014: 18) defines the difference between the two models as follows: "the social network model involves a quantitative, structural view of a practice, whereas the CoP includes both qualitative and quantitative measures and shows how the structure influences learning (and vice versa)". Although Witten is arguably underestimating the extent of the qualitative work undertaken by SNA researchers to understand the meanings and implications of their quantitative findings, her point that the CofP framework more explicitly allows for both qualitative and quantitative analysis remains relevant. Despite Meyerhoff and Strycharz (2013: 435) writing that the CofP framework has been used "less often" than expected in twenty-first-century linguistic research, there is nevertheless a modest body of work demonstrating its usefulness to the discipline. Many
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linguistic studies utilising the CofP framework can broadly be divided into three interrelated strands: language and gender, variationist sociolinguistics, and discourse analysis. The CofP model made a significant theoretical contribution to the study of language and gender when first introduced to the linguistic discipline by Eckert and McConnell-Ginet (1992a; 1992b) in the 1990s. In fact, Bucholtz (1999: 221) writes that the framework "revolutionised the field of language and gender". One of the main attractions of the theory is that it encourages researchers to consider the social practices and contexts in which language and gender are constructed (Eckert & McConnell-Ginet 1992a). In subsequent years, most linguistic studies that have adopted the CofP framework have focused, in some way, on gender (Meyerhoff & Strycharz 2013: 439). For instance, research has found a correlation between CofP membership, language variation, and gender (Eckert 2000), language variation in same-gender CofPs has been studied extensively (Alam 2015; Mendoza-Denton 2008; Lawson 2009; Lawson 2011; Moore 2003), and qualitative studies have used the CofP framework to explore the discourses of same-gender groups (Bucholtz 1999; Moore 2006; Ostermann 2003). The second linguistic subspecialty to embrace the CofP framework is variationist sociolinguistics. Many variationist studies have made use of the CofP model to explore the relationship between language variation, social identity, and non-linguistic phenomena. This branch of research was arguably pioneered by Eckert (1988; 2000) in her ethnographic study of language variation in a suburban Detroit high school. Eckert identified two distinct communities of practice: the Jocks and the Burnouts. She found that the Jocks and Burnouts, as well as partaking in contrasting non-linguistic social practices (such as fashion choices, career trajectories, and levels of engagement with school activities), also differed significantly in the extent to which they were participating in the Northern Cities Chain Shift. Eckert's work here is significant as she demonstrated that the linguistic variation observed had to be considered in light of other social practices and could not be explained by looking at macro-sociological factors such as class or gender alone. Eckert's research inspired a wave of variationist studies that adopted a similar methodology (Alam 2015; Lawson 2009; Lawson 2011; Mendoza-Denton 2008; Moore 2003). That is, the researcher undertook extensive ethnographic work in a high school, documented the existence of one or more CofPs defined by a set of social practices (typically including fashion choices, extracurricular activities, and level of engagement in age-restricted behaviour such as smoking and drinking), and found a correlation between membership in a CofP and the use of linguistic variants. 25
The final linguistic subspecialty which has embraced the CofP framework is discourse analysis (Donath et al. 2005; Freed 1999; Holmes & Woodhams 2013; King 2014; Ostermann 2003; Willems 2017). King (2014: 62) writes that the CofP framework "is in a strong position to enable insight into the inner workings of a community's discourse-driven formation and maintenance". For instance, Ehrlich (1999) explores how a CofP of tribunal members hearing a sexual harassment case draw on their shared repertoire of questioning practices and shared assumptions about how the victims should have behaved during the alleged attacks to undermine the victims' narratives and recast them as complicit in their own victimisation.
Communities of Practice and language creativity
Wenger (1999) argues that CofPs are "a likely locus of creativity" (289) and states that "propagation of innovation" (125) is one of the key indicators that a community can be considered a community of practice. He goes as far as to write that "if there is hardly any local production of negotiable resources, and if hardly any specific points of reference or artifact are being created" then the community in question may not qualify as a CofP (Wenger 1999: 126). Perhaps unsurprisingly, then, many CofP studies have explored creative practices, from home brewing (Knearem et al. 2019) to quilt making (Launspach 2017). As well as being associated with creative practices broadly defined, Wenger (1999) also seems to suggest that CofPs are sources of language creativity. He argues that CofPs can be recognised from the existence of a shared linguistic repertoire consisting of "jargon and shortcuts to communication as well as the ease of producing new [shortcuts]" (Wenger 1999: 125). Despite this, however, language creativity in CofPs has not generated a great deal of research. Most of the CofP work that could broadly be categorised as investigating language creativity has been conducted under the heading of variationist sociolinguistics (see Section 2.4) and has thus been interested in the social differentiation of linguistic variants, typically among communities of adolescents. Beyond this realm, work directly related to language creativity in CofPs is relatively rare. Nevertheless, Wenger's conceptualisation of language creativity as a part of the day-to-day practices of a CofP has parallels with the body of work on 'everyday language creativity'. Much of the formative research on language creativity was dominated by the stylistic study of literary creativity (Fowler 1996; Leech & Short 1981; Toolan 1998). However, over
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the past thirty years, there has been a growing interest (see Carter 2004; Jones 2012; Swann & Maybin 2007; Tannen 1989) in everyday language creativity, which sees creativity as an "all-pervasive feature of everyday language" (Carter 2004: 13). Swann and Deumert (2018: 1) write that this emergence is part of a broader movement in the social sciences which has seen creativity cease to be primarily associated with talented literary writers or professionals working in creative industries and come to be regarded as a practice that all humans are capable of. This ideological re-evaluation has been referred to as the "democratisation of creativity" (Maybin & Swann 2007: 497). The rise in the study of everyday language creativity is, arguably, in part at least, linked to the contemporary interest in language creativity in computer-mediated communication (CMC) environments. CMC is defined as "an umbrella term that encompasses various forms of human communication through networked computers, which can be synchronous or asynchronous and involve one-to-one, one-to-many, or many-to-many exchanges of text, audio, and/or video messages" (Lee & Oh 2015: n.p.).1 Since the study of CMC began in earnest in the 1990s (Herring, Stein & Virtanen 2013), everyday language creativity in CMC has been a recurring theme in research from a variety of disciplines. In fact, some studies have concluded that CMC is intrinsically creative (Crystal 2006; Danet 2001; Danet, Ruedenberg‐Wright & Rosenbaum‐Tamari 1997). Consequently, researchers have attempted to articulate why CMC fosters high levels of language creativity. Danet (2001), for example, proposes four factors which contribute to the creative nature of CMC. The first is the interactive and immersive nature of the digital medium, in which users can communicate synchronously in written or multimodal formats. The second factor is the influence of linguistically creative 'hackers' who were among the earliest internet users. Third is the perception of the internet (at the time she was writing at least) as an open-frontier with few established norms or rules. Finally, Danet proposes that the anonymity afforded to users online "freed participants to behave in novel ways, or to explore aspects of their personality which had hitherto gone unexpressed" (see also Lazaraton 2014 on the relationship between creativity and CMC anonymity). Furthermore, Herring, Stein and Virtanen (2013: 8) propose that "the written, persistent nature of CMC makes language more available for metalinguistic reflection than in the case of speech" and this, when combined with the "tendency towards
1 Alternatives to the term ‘CMC’ have been proposed which reflect that some of the digital communication labelled as CMC does not technically involve computers. For instance, Lewin-Jones (2015) opts for “digital communication”, Androutsopoulos (2011) for “digital networked writing”, and Thurlow and Bell (2009) for “new media discourse”. However, I follow Herring, Stein and Virtanen (2013) in choosing to use the term CMC as it is the most widely accepted name in the literature for the phenomena defined above. 27
loose cross-turn relatedness in multiparticipant CMC", encourages creative language practices. A prominent theory for defining and conceptualising creativity in the everyday language creativity tradition that, I argue, is broadly compatible with the CofP framework is Maybin and Swann's (2007) dynamic framework, which proposes that there are three interconnected dimensions to language creativity. The first is the textual dimension which is concerned with the linguistic forms that creative language practices take. Typically, definitions of creativity note that there must be some element of novelty present to qualify for the label (Richards 2010: 189; Sternberg & Lubart 1999: 3). However, language creativity researchers seem to concur that creativity does not necessitate truly novel (that is, never seen before) linguistic forms, but can be "new combinations of existing elements" (North 2007: 539) or established elements playfully "deployed so as to be relevant to the unfolding context" (North 2007: 542; see also Lewin- Jones 2015). In CofP terms, the textual dimension is intrinsically linked to how creativity manifests formally in the shared linguistic repertoire of the community. The second aspect of Maybin and Swann's (2007) framework is the contextual dimension, which considers the sociohistorical and interpersonal circumstances in which creativity takes place. This dimension then is concerned with factors such as the purpose of the creativity, the co-construction of creativity among participants, and the social, technological, and cultural resources that make the creativity possible (Maybin & Swann 2007: 512-513). Additionally, through a CofP lens, we can also consider how the practices and the joint enterprise of the community lead to the emergence of the creative forms. The third and final component is the 'critical dimension' which is concerned with "the potential for linguistic creativity to foreground, in various ways, the kinds of critical/evaluative stances that are evident in all language use" (Maybin & Swann 2007: 498). This dimension is associated with instances of language creativity which intersect with social relations, dominant power structures, and established values or norms (typically by critiquing or subverting them). In CofP research, the critical dimension can be drawn upon to explore the intersection between language creativity, hierarchy, and power in online CofPs, an area which is key to the current research.
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Communities of Practice and power
Arguably, the most significant area of controversy in the CofP framework centres on issues relating to power, status and hierarchy. Given the scope of this debate, this section of the literature review is split into five sub-topics. The first two sub-topics briefly contextualise the issue through an exploration of the sometimes problematic definitions (or lack thereof) of power in the existing literature and also the studies which have questioned the extent to which the framework is capable of modelling community power dynamics. The third sub- topic considers the role of the weak-tie theory of language change in the CofP framework, while the fourth looks at the relationship between hierarchy, status, and power in CofPs. The fifth and final sub-topic explores the intersection between power and LCM in online CofPs.
Issues with linguistic definitions of power in the Community of Practice framework
Across the linguistic CofP literature, a recurring problem is that power is either treated as a self-explanatory concept or, at best, is only vaguely defined by the researchers. These issues are not unique to CofP theory and are, in fact, criticisms of the study of power across linguistics and the social sciences more generally (Dunbar 2015; Kucherenko 2016; Turner 2005; Spencer-Oatey 1996). Indeed, Thornborrow (2014: 5) refers to power as a "conceptual can of worms", while Spencer-Oatey (1996: 22) writes that "few linguists explicitly discuss the conceptual nature of" power in their work. For example, Eckert & Wenger (2005) reject the idea that power in CofPs is necessarily top-down and hierarchical, making the point that power structures can take many forms. However, they do not explicitly define what they mean by power. Nevertheless, in some of the studies outlined in Sections 2.5.3 and 2.5.4 below, it is possible to infer the authors' definitions of power from their argument. In Davies (2005), for instance, power is top-down, hierarchical, and it is implicitly defined as the ability to influence and control: power is something that can be 'wielded' by a few over the many. Moore (2005), instead of using the term 'power', primarily discusses 'status' in her narrative analysis work: her CofP of interest is marked by status inequalities. The member with the highest status is the most dominant figure in the community. However, she does not have unilateral control over the community and its resources: all legitimate members of the CofP can contribute to the
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community's negotiation and practices. So, again, power/status appears to be implicitly linked to control, but in a more limited way than proposed by Davies (2005). Going forward it is clear that research hoping to contribute to the body of work on power in CofPs must take as its starting point an explicit definition of power which is relevant and meaningful to the community under discussion. I discuss my approach to power (and related concept such as status and hierarchy) in detail in Section 3.4.2. However, for now, it will suffice to say that, in this work, power is defined as the ability to consciously or unconsciously control or influence other people's behaviour in a specific social context.
The Community of Practice framework and the handling of power.
One of the most notable debates within CofP theory centres on the framework's ability to model power dynamics. Critics (including Contu & Willmott 2003; Fox 2000; Kendall 2008; Li et al. 2009; Paechter 2006; Salminen-Karlsson 2006) argue that Lave and Wenger failed to adequately describe and model power in their accounts of the theory. Contu and Willmott (2003), for instance, contend that Lave and Wenger partially lay the theoretical groundwork for considering issues relating to power, but they then marginalise discussions of power in the CofP case studies exemplified in the second half of their work. Lave and Wenger (1991: 86), however, are aware that they neglect power: they refer to their ethnographic case-studies as being "on the whole silent" about issues related to power and control, especially concerning newcomers' access to a community. They conclude that, in future work, "unequal relations of power must be included more systematically in our analysis" (Lave & Wenger 1991: 42). Nevertheless, the extent to which either author has returned systematically to this issue is debatable. A recurring criticism of Wenger's 1998 volume on the CofP framework, for instance, is that power relations are not satisfactorily explored (Fox 2000; Salminen-Karlsson 2006). Nevertheless, several publications (Eckert & Wenger 2005; Gee 2005; Moore 2006; Moore 2010; Wenger 2010) have contended that although power is not – and was never intended to be – the primary focus of the CofP model, it is still intrinsically bound with many of the components central to the theory. Indeed, below I outline several studies which have demonstrated that the CofP framework is compatible (although not always unproblematically) with explorations of power, status, and hierarchy.
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The Community of Practice framework, power, and the weak-tie theory of language change
Davies (2005) argues that linguistic influence correlates with one's position in the hierarchy of a community, with the people at the top having the power to veto and control the community's linguistic resources. In Davies' conceptualisation, peripheral members of a CofP are extremely low in the vertical hierarchy, and thus she finds it difficult to envision how they could be influential enough to affect linguistic diffusion and variation in the community. To resolve this tension, she recommends that the CofP framework borrows the SNA distinction between peripheral innovators and central early adopters. SNA theory holds that innovations are introduced by peripheral individuals with weak-tie connections to the network (Milroy & Milroy 1985). For an innovation to be successful, it must then be adopted by central figures, and from these influential 'early adopters' it will diffuse out to the rest of the community (Milroy & Milroy 1985). These principles, collectively known as the 'weak-tie' theory of language change, have been found to hold in studies of both contemporary and historical social networks (Ash & Myhill 1986; Labov 1972b; Milroy & Milroy 1985; Tieken-Boon van Ostade 1991). Findings have been more mixed, however, in online social networks. For instance, Huffaker (2010), in his statistical analysis of factors which contribute to social influence, found that brokers (that is, those with weak ties to different groups) did not significantly influence language diffusion in an online community. Meanwhile, Bergs (2006: 13) argues that, in the context of online social networks, "innovations now come from within, from the central network members, not from bridges or marginal positions". He concludes that central figures in online networks are uniquely privileged in their ability to introduce and diffuse innovations through their network, posing a contrast to the idea that innovations will be introduced by weak-tie, peripheral individuals. Bergs' theoretical hypothesis was later supported by empirical evidence from Kooti et al. (2012), who found that the innovators of the linguistic conventions used to indicate that a message was being retweeted on Twitter were among the most active, well-connected users on the platform. Therefore, while the weak-tie theory of language change appears to be relatively unproblematic in offline contexts, there may be issues of generalisability in online networks. Davies' SNA-inspired theory envisions language innovation and diffusion in CofPs working as follows: peripheral members introduce innovations into a community, but the
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innovations only successfully diffuse if they are accepted and adopted by the leaders/central figures in the CofP. There is support in the literature for the idea that peripheral members' innovations need to be sanctioned by more central members of a CofP. For instance, Bucholtz studies a potential "cultural and linguistic broker" (1999: 219), Carrie, who attempts to introduce slang terms used by cooler students into a CofP of 'nerdy' girls (of which she is a peripheral member) in a California high school. However, the girls do not accept the slang terms into their vocabulary, labelling them "Carrie words" and even ridiculing her use of the terminology (1999: 219). Bucholtz's findings, here, support the idea that a peripheral member cannot successfully diffuse an innovation through a community unless it is accepted by more high-status members. Moore (2010) also explores the idea that peripheral members serve as innovators. She argues that the changes in the frequency and usage of tag questions in two British high school CofPs are likely directly associated with the peripheral and marginal members who "offered lines of communication which facilitated this sociolinguistic shift" (2010: 132). Here, then, unlike in Bucholtz (1999), peripheral members are successful in diffusing variants into a CofP, and Moore consequently contends that "peripheral speakers (and, indeed, peripheral techniques) must become central" in sociolinguistic investigations (Moore 2010: 133). However, what Moore does not explore is why the brokers are successful. The broker in Bucholtz (1999) 'failed' because her innovations were rejected and mocked by the full members of the community. It could be the case that the peripheral members in Moore (2010) were only successful because high-status members of the community embraced the incoming variants. However, this is not determinable from Moore's published analysis. The only study to consider the weak-tie theory of language change's applicability to an online CofP is Stewart et al. (2017). This research offers support for the idea that peripheral members introduce innovations through an exploration of language variation in a pro- anorexia Instagram CofP. Stewart et al. (2017) found that newcomers to the CofP drive the changes and introduce innovative spelling variants into the network. Committed members then take on the role of early adopters, being 4.33% more likely to adopt innovations than more transient members of the community (a finding that a t-test finds significant at p < 0.001). However, it should be noted that there may be a difference in the type of peripheral members discussed by Stewart et al. (2017) and those discussed in the research above. In the Instagram community, the innovative members were peripheral because they were 32
newcomers on an inbound trajectory into the community. In contrast, the peripheral individuals in Moore (2010) and Bucholtz (1999) were seemingly on a permanent peripheral trajectory with either no ambition or no opportunity to become full members. Furthermore, this study was grounded in an unusual linguistic context as the researchers focused only on the innovation of variants of banned or restricted terms on the Instagram platform. Members of the community who wanted to make their pro-anorexia content discoverable and searchable (such as newcomers who did not already have a large following on the site, for instance) had to use orthographic variants of the restricted terms. Overall, then, this study contributes to the evidence that peripheral members of a CofP are innovators (and it is, to the best of my knowledge, the only study of an online CofP to do so). However, the context- specific nature of this research should be considered when attempting to generalise the findings. Also offering support for the idea that the weak-tie theory of language change is relevant to the CofP framework are studies which have explored the positions of individuals who are the most notable leaders of language change in a CofP. In her Detroit high school study, Eckert (1988; 2000) found a correlation between language variation and the extent to which one engages in (and is committed to) the practices of a CofP. To exemplify, she found that the Burnout girl with the most innovative speech patterns was the most 'extreme' Burnout (in that she most thoroughly embodied the practices of the Burnout CofP: she dressed like a Burnout, took drugs, and spent a significant amount of times in urban areas). In contrast, the Burnout with the most conservative speech was also the most conservative in terms of her participation in Burnout practices. Similarly, Mendoza-Denton (2008) in her ethnographic work with female gang members at a California high school, found that the realisation of /I/ varied depending on if the speaker was a core or peripheral member of the CofP. Like Eckert before her, she concluded that "the most extreme behavior in the vocalic system corresponds to community members who had the most extreme behavior in the social system" (Mendoza-Denton 2008: 256). She evokes Eckert's concept of iconic speakers, who are defined as "socially salient individuals toward whom others orient, and who become salient and imitated as a result of their extreme behavior, centrality within their group, and broad social ties" (Mendoza-Denton 2008: 210). Specifically, she argues that the most iconic speakers in the CofPs studied were the leaders of the gangs: these girls most thoroughly embodied the ideology of the gang and they were the ones leading the raising of /I/ in their CofPs (Mendoza-Denton 2008: 255-256). Mendoza-Denton's work, then, suggests that linguistic variation will be advanced by the 33
'leaders' of the community: the most central individuals who most thoroughly embody the practices of the community. This conclusion is in line with the weak-tie theory of language change, which argues that it is the central, influential individuals who will lead changes and diffuse innovations. To summarise, then, there is plentiful evidence from studies of offline CofPs to support Davies' (2005) hypothesis that the weak-tie theory of language change is helpful when considering innovation and diffusion in a CofP (Bucholtz 1999; Eckert 1988; Eckert 2000; Mendoza-Denton 2008; Moore 2010). However, the only study to test if the weak-tie theory is applicable to online CofPs (Stewart et al. 2017) is grounded in an unusual and ungeneralisable linguistic context. Therefore, it is not clear if the two general principles of the weak-tie theory of language change (that is, that innovations are introduced by peripheral members and diffused by high-status early adopters) will also apply to online CofPs or if similar issues will be encountered as when the weak-tie theory was applied to online social networks (Bergs 2006; Huffaker 2010; Kooti et al. 2012).
The Community of Practice framework, power, status, and hierarchy
The second issue which is critical to this thesis centres on the ongoing debate regarding the relationship between power, status, and hierarchy in the framework. Broadly, work in this area takes one of four positions, each of which is discussed below. The first view is that CofPs have 'horizontal' power structures (Wenger 2010; Kerno 2008). The second contends that CofPs are composed of top-down hierarchies, where the small number of people at the top have power over those who are lower down in the hierarchy of the community (Davies 2005; Silva, Goel, and Mousavidin 2009). The third view contends that CofPs can have top- down hierarchical structures, but hierarchical rankings will not necessarily correlate with power, and any legitimate member may have power in the community (Moore 2006). The fourth and final view suggests that the relationship between power and hierarchy may be more fluid and less straightforward than acknowledged in the other three views (Mak & Chui 2013; Wilson 2009).
View 1: CofPs have horizontal power structures
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In his writings on CofPs in an institutional context, Wenger (2010: 195-196) distinguishes between two types of power. The first, vertical accountability, is rooted in top-down hierarchical structures, whereas the second, horizontal accountability, is associated with mutual engagement, joint activities, identity, and negotiation. It is the second type of power, Wenger argues, that can be found in CofPs. Wenger's conclusions here are in line with Kerno (2008: 76), who argues that the hierarchical structures of corporations are incompatible with the "flatter, horizontally linked" structures that he believes are characteristic of CofPs; he argues that vertical hierarchical structures represent a "challenge" to the CofP approach. However, the argument that there are no top-down/vertical hierarchies in CofPs is problematic. Studies of both offline and online CofPs have provided examples of communities which meet the defining criteria for a CofP that have, to a greater or lesser extent, some element of a top-down hierarchy in place (Eckert & Wenger 2005; Silva, Goel & Mousavidin 2009; Moore 2006). For instance, Eckert's study of the CofP of Jocks in her Detroit high school study documented the existence of a top-down power hierarchy, in which all members had a place and a correlated degree of power (Eckert & Wenger 2005: 585). Therefore, in the context of sociolinguistic research, as opposed to the organisational context which framed Wenger (2010) and Kerno's (2008) work, this view of exclusively horizontal structures may well be an oversimplified account of the dominant power relations.
View 2: CofPs are composed of top-down hierarchies The juxtaposing view to the one outlined above is the notion that CofPs are composed of top- down, vertical power structures. A study that advocates for this position is Silva, Goel, and Mousavidin (2009). The authors find that long-term community members often act as gatekeepers and covertly or explicitly criticise newcomers to an online community who unwittingly flout established practices or make low-quality posts. They consequently argue that online CofPs need to take the form of top-down, vertical hierarchies, where either volunteer content moderators, or the sub-community of long-term members, oversee community activity and discipline nonconformists (typically newcomers). Silva, Goel, and Mousavidin (2009: 73) write that their advocation for top-down power in online communities is not concordant with the CofP framework, which they believe contends that hierarchy would hinder "the creation and dissemination of knowledge". However, they maintain that structure and hierarchical power dynamics are necessary to maintain community coherence and purpose. Although their conceptualisation of power in online CofPs appears to be generalised from their research on just one community, it should 35
be noted that several other studies of online CofPs (e.g. Kendall 2008; Paechter 2006; Stommel & Koole 2010) have suggested that a hierarchical system is in place, especially in terms of the asymmetrical relationship between newcomers and long-term members. Nevertheless, Silva, Goel, and Mousavidin's (2009) argument that online communities need hierarchical structures so that established members can act as gatekeepers and discipline newcomers is potentially problematic from a theoretical perspective. Indeed, it is a fundamental principle of the CofP framework that new members, in bringing their identity, agency, and past experiences to the CofP, may alter the community as they contribute to the continued negotiation of practice and meaning (Wenger 1998: 101; 157-158). If newcomers are disciplined every time they deviate from existing norms, it is not clear how they would be able to influence or contribute to the emergence and renegotiation of practices. Perhaps the most high-profile linguistic study advocating for the top-down hierarchy theory is Davies (2005), who contends that a hierarchical structure is necessary to manage access to and participation within a CofP. She argues that in order to undertake legitimate peripheral participation, on the course to becoming a full member of the CofP, individuals must first receive "sanction from within the hierarchy" of the community (Davies 2005: 577). With this notion, Davies seems to be envisioning CofPs as having a top-down vertical power structure, in which individuals who are at the top of the hierarchy act as gatekeepers and can decide if new members should be allowed to join the community. To support her argument, Davies cites the following passage from Eckert and McConnell-Ginet's (1995) discussion of the first author's Detroit high school study:
What is essential for jock girls is approval from those already prominent; especially but not only boys. To be seen by those able to grant entry to the inner circle as desiring such entry is to jeopardise the chances of getting it (Eckert & McConnell- Ginet 1995: 492).
Davies (2005: 571-572) uses this extract to argue that a) vertical hierarchies do exist in CofPs, b) both outsiders and members of the CofP are aware of and accept the hierarchy and are also able to recognise individuals at the top of the social structure, and c) the small number of individuals at the top "wield" power over those who are lower down in the hierarchy. Davies contends that the current incarnation of the CofP framework does not allow one to model or conceptualise hierarchy, and she concludes that the framework, as used in linguistic studies at least, needs to be adapted to (better) incorporate hierarchy and related 36
concepts such as gate-keeping, legitimate access to the community, and acceptance of new members (Davies 2005: 557). Just as viewpoint 1 is too simplistic in arguing that power in CofPs can only be conceptualised as 'horizontal', viewpoint 2, as discussed below, has also been criticised for oversimplifying the complex nature of power in CofPs.
View 3: Any legitimate member can have power in the community, regardless of their position in the hierarchy A study which is particularly critical of elements of View 2 is Moore (2006), who is particularly interested in Davies' implication that individuals higher up in the hierarchy of a community will have control over the community's resources, while more marginal individuals will be excluded, by the very nature of their peripherality, from full access. Moore (2006) explores this hypothesis by using narrative analysis methodology to look at how CofP members of unequal status narrate a story and negotiate community practices. Moore's data is drawn from her ethnographic study of female students at a high school in Greater Manchester, and her analysis focuses on a single conversation between three teenage girls, Ellie, Meg, and Kim. Ellie was widely identified as a central figure within the CofP of 'townies' (characterised by their preference for heavy make-up, designer clothing, and their engagement in age-restricted activities such as drinking, smoking, and sex) and fulfilled the role of a sociolinguistic icon (Moore 2006: 617). Because of this, Moore argues that if Davies' hypothesis regarding the role of CofP members at the top of the hierarchy is correct, then Ellie should be able to "control Townie identity in ways that her Townie peers cannot" (Moore 2006: 617). However, Moore shows how Ellie and Meg, a member lower in the hierarchy of the community, both successfully convey their sometimes-competing narratives, despite their unequal status in the CofP. Ellie was the most dominant storyteller, but Meg was able to hold the floor (albeit typically after competing for the right). Consequently, Moore argues that "there may be a hierarchy of narrators, but both narrators are entitled tellers" (2006: 633). In contrast, the outsider, Kim, who had only marginal ties to the community was not allowed to hold the floor: her attempts at topic-shifting were rejected, and both Ellie and Meg acted as gatekeepers and excluded Kim from the conversation. Kim was not allowed to participate in the narrative because she was not considered a legitimate member of the community.
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Moore does not refute Davies' hypothesis that CofPs may have vertical hierarchical structures. However, she does contest the idea that individuals at the top of the hierarchy will have control over a community's resources, while legitimate members lower in the hierarchy are excluded from full access. The most powerful people in a community do not individually control the community's resources and access, she argues: all legitimate members, regardless of their status, can contribute to the community's negotiation and practices (Moore 2006). However, although Moore's extensive analysis here is convincing, it is nevertheless based on a single (albeit, in Moore's opinion, representative) conversation between members of one community. To generalise these findings further, it would be necessary to explore if these power dynamics hold across different CofPs.
View 4: Views 1-3 are too simplistic in their conceptualisations of the relationship between power and hierarchy. Eckert and Wenger (2005) contend that the CofP framework does not presuppose that power relations within a CofP will take "a stratified structure that confers power according to positions" of the kind proposed by Davies in View 2 (Eckert & Wenger 2005: 582). Furthermore, they note that the model does not assume that one will be able to predict the most powerful people by looking at the structure of the community. The top-down approach advocated for by Davies would, they argue, oversimplify the multitude of ways that power and hierarchy may operate in CofPs. Helpfully, Eckert and Wenger (2005: 585-586) exemplify how two CofPs can have different hierarchical structures by referring to Eckert's Detroit study. The Jock CofP had a vertical power hierarchy, where the people at the top were the most popular and the most powerful: this hierarchy was consensual and accepted by members and outsiders alike. In contrast, in the Burnout CofP, their "very strong egalitarian and anti-institutional ideology militate[d] against an integrated status hierarchy" (Eckert & Wenger 2005: 586). In other words, in the Burnout CofP, there was not a vertical power structure comparable to the Jocks', in which all members had a place and a correlated degree of power. Eckert and Wenger conclude that the power structure in a CofP emerges dynamically via interaction and negotiation, as opposed to conforming to a pre-ordained and universally applicable structure. Consequently, they argue that ethnographic studies of each CofP of interest need to be undertaken to understand the power structure within that community. Notably, however, this argument does seem to contradict Wenger's later work (Wenger 2010), where, as outlined above, he unequivocally equates CofPs with horizontal power structures. His earlier 38
conceptualisation, described here, is arguably a more nuanced approach to the study of power in CofPs. Another study which problematises Views 1-3 is Mak & Chui (2013), who adopt a workplace discourse analysis approach to investigate the negotiation of power in an online CofP formed on Facebook by employees of a Hong Kong restaurant. The researchers take a social-constructivist approach, which leads them to envision power as a dynamic, versatile, and changing phenomena. They find that in the CofP of interest, the typical workplace hierarchy is re-negotiated, manipulated, and even subverted. Subordinates lecture and mock their superiors, and a newcomer to the business publicly exposed their superior as dishonest. They write that in the online CofP "the institutional authority, official hierarchy and predetermined status" becomes "fluid and open to reconstruct" (Mak & Chui 2013: 100). Similarly, Wilson (2009) examines how the captain of a Scottish rugby team manages his complicated place in the hierarchical structure of the CofP, which sees him take on the roles of the deputy leader of his team, a fellow player, and also the subordinate to the coach. Wilson finds that the captain adopts different strategies as needed, which either enforce or minimise his status in the hierarchy. Through this case study, Wilson exemplifies that power and status are not fixed and stable concepts in CofPs, and the ways in which, and the extent to which, power and status are performed and reinforced are also changeable and context- dependent. It would seem that the most crucial point to take away from the studies outlined under the heading of View 4 is that CofPs may consist of dynamic and fluid power relations. Any investigation of power structures, then, must be open to the idea that power can be fluid and changeable and that the relationship between power and hierarchy may not be straightforward.
The Community of Practice framework, power, and content moderation.
The final subtopic to be explored is the relationship between the CofP framework, power, and linguistic content moderation (LCM). Content moderation is defined as "the organised practice of screening user-generated content […] posted to internet sites, social media, and other online outlets, in order to determine the appropriateness of the content for a given site, locality, or jurisdiction" (Roberts 2017: n.p.). Typical motivations for content moderation on
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mainstream platforms are to remove illegal, objectionable, or inappropriate content, such as copyrighted material, hate speech or pornography (Cai & Wohn 2019a; Chancellor et al. 2016). On some online platforms (such as Twitter and Instagram), content moderation is performed by commercial content moderators who have been hired by the owners of the website to specifically enforce the site rules (Cai & Wohn 2019a). On other sites, such as Wikipedia and Reddit (and thus Popheads), commercial content moderators are replaced or complemented by volunteer content moderators. Unlike commercial content moderators, who may not consider themselves members of the community they monitor, typically volunteer content moderators are dedicated members of the community and have been trusted with the role because they have proven themselves reliable (for instance, through long-term membership and prolific or highly valuable contributions). Popheads operates LCM policies (in which certain words and expressions are banned in the community), and the introduction and aftermath of these policies on the internal power dynamics of the community is a key focus of my research. The literature reviewed below focuses on the elements of LCM that are relevant to the current study: that is, where content moderation has led to users employing linguistically creative methods to circumnavigate moderation policies. This is an inherently subversive type of language creation as it involves users employing strategies to evade, defy, or subvert content moderation policies enforced by individuals or organisations with high degrees of power (be it the government, the employees of the website that they are using, or members of their own online community). To the best of my knowledge, the only studies which have explored the linguistic effects of content moderation on a community of practice are Chancellor et al. (2016) and Stewart et al. (2017)'s explorations of an Instagram CofP which promotes eating disorders (that is, a 'pro-anorexia' community). In 2012, in response to concerns about the glamorisation of disordered eating practices, Instagram began preventing posts containing words and hashtags associated with the promotion of eating disorders (for example, thighgap, thinspiration, probuilima, and proana) from displaying in search results. Instagram's content moderation policy, then, was not to ban pro-anorexia words: posts containing the forms were not removed, but rather the platform was configured in such a way as to make the content hard to discover. Consequently, members of the pro-anorexia CofP who wanted to make their posts discoverable and searchable began to use orthographic variants of the moderated tags (for instance, thyghgapp) to bypass the content moderation efforts. Chancellor et al. (2016) found that the variant spellings both increased in frequency over time following the ban and became more creative (that is, more distinct from the original word). They conclude their 40
research by arguing that the content moderation policy enforced by Instagram was ineffective and may be putting users at more risk as the variants isolate the pro-anorexia community from more 'mainstream' Instagram users, turning the community into an echo chamber. Working with the same dataset, Stewart et al. (2017) later found that it was newcomers to the pro-anorexia Instagram community that were driving the changes and introducing innovative spelling variants into the network. 'Committed' members then took on the role of early adopters. They also found that there was a weak correlation between the level of orthographic creativity and the amount of social attention (in the form of "likes") that a post received from fellow community members, suggesting that this subversive form of language creativity can earn the practitioners a certain amount of social capital from fellow members. Although the above is the only study exploring the linguistic consequences of content moderation in a CofP, a small amount of research on this topic has been conducted on platforms that most probably do not meet the criteria of a CofP. The earliest study comes from psychologists Suler and Phillips (1998) who looked at the consequences of moderating expletives in an online chatroom as part of their research into deviant behaviour online. The owners of the chatroom had programmed it to transform any expletives into asterisked variants (e.g. f**k); however, they note that some members used variant spellings (such as fuq, phuk) to bypass the script. Interestingly, this linguistic practice is attributed by the authors to "creatively mischievous users" (Suler & Phillips 1998: 291). Much of the recent research on linguistic creativity and content moderation has focused on state-imposed internet content moderation in China. Indeed, in response to state- sanctioned content moderation, some Chinese web users wishing to discuss sensitive topics employ a range of phonological, morphological, and orthographical linguistic strategies to circumnavigate the websites' attempts at content moderation (Chen, Zhang & Wilson 2013: 20; Hiruncharoenvate, Lin & Gilbert 2015; Wozniak 2015). The work cited above comprises, to the best of my knowledge, all of the studies to date on the relationship between content moderation and linguistic creativity. However, it should be noted that all of the studies above focus on exogenous content moderation enforced by commercial content moderators. Forces from outside the community (be it the government or the websites' staff) have put in place rules and guidelines that community members are expected to conform to. To the best of my knowledge, there has been no work on linguistic creativity as a response to endogenous content moderation: that is, where members of a community have put in place rules about acceptable content, which are then enforced by other members acting as volunteer content moderators. This is a very different research 41
context, and it will be interesting to explore how the norms of endogenous content moderation are negotiated by community members and also the effects of linguistically creative content moderation defiance strategies on the internal power dynamics of a CofP.
Conclusion
In Sections 2.2 and 2.3, I outlined the general principles of the CofP framework and demonstrated that online communities can meet the necessary criteria to be considered CofPs. Next, Section 2.4 looked at how the CofP model has been used by discourse analysts exploring the inner workings of communities and also sociolinguists seeking to understand the relationship between language and social practices. Section 2.5 then considered the role of linguistic creativity in CofPs. In Section 2.6, I provided an overview of existing literature on the role of power in CofPs. Firstly, I explored how power is often poorly defined by CofP researchers, and I then critically evaluated the argument that community power dynamics cannot be conceptualised using the CofP framework. Next, I explored the applicability of the weak-tie theory of language change to CofPs. Davies (2005) proposes that the SNA-inspired hypothesis that innovations are introduced by peripheral members and need to be sanctioned by full members before they diffuse through the community should be incorporated into the CofP framework. Several studies of offline CofPs have provided support for this hypothesis (Bucholtz 1999; Mendoza-Denton 2008; Moore 2010). However, the only research to have looked at the applicability of the weak-tie theory to online CofPs is Stewart et al. (2017), and that study was situated in a potentially ungeneralisable linguistic context. An open question, then, is whether the weak-tie theory of language change is applicable to online CofPs or if it will face the same issues as some researchers have documented (Bergs 2006; Huffaker 2010; Kooti et al. 2012) when they try to apply the weak-tie theory to studies of online social networks. The first three research questions explored in this work thus consider the extent to which the weak-tie theory holds in an online CofP:
RQ1.1 Does the weak-tie theory of language change's prediction about linguistic innovators hold in an online CofP?
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▪ H1.1. Peripheral members will be the innovators of linguistic forms.
RQ1.2 Does the weak-tie theory of language change's prediction about early adopters hold in an online CofP?
▪ H1.2. Members with high-status will be the early adopters of linguistic forms.
RQ1.3 Which status markers (if any) are statistically significant predictors of early adopter status?
▪ H1.3 All status markers will be statistically significant predictors of early adopter status.
I then looked at the ongoing debate regarding power and hierarchy in the CofP framework. Broadly, the four views can be summarised as follows: 1) CofPs are composed of horizontal power structures; 2) CofPs are composed of vertical structures and those at the top control and influence the community and its resources; 3) CofPs are composed of vertical structures but any member can control and influence the community and its resources; and 4) the relationship between power and hierarchy may be more complex than allowed for in any of the above views. Finally, I considered work which explores the subversive form of language creativity that arises from users evading and defying online content moderation policies (Chancellor et al. 2016; Chen, Zhang & Wilson 2013; Stewart et al. 2017; Wozniak 2015). All of the work in this area to date has focused on exogenous content moderation, where content moderation policies are put in place by community outsiders. There has not yet been a study of a scenario such as that found in the Popheads community, where some members have created a list of banned words which the rest of the community are expected not to use. In this scenario, it is members of the community who are enforcing content moderation policies, while also simultaneously participating as legitimate members of the community whose language they are 'moderating'. This is an interesting sociolinguistic context, and my research considers the impact this scenario has on the internal power dynamics of an online CofP. Specifically, in this research, I analyse the relationship between power, status, and hierarchy by exploring the control and negotiation of linguistic forms subject to endogenous linguistic content moderation (LCM) policies. This approach was chosen, in part, to further the understanding of the power dynamics which shape and control the shared repertoire of a
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linguistically creative online CofP. A second motivation is that I wish to contribute to the study of LCM, which, to date, has only been investigated in exogenous contexts.
The research question explored is:
RQ2: Who has the power to control or influence linguistic resources in the Popheads CofP?
The hypotheses related to this research question have mostly been derived from the distinct – and non-compatible – conceptualisations of power proposed in the CofP literature:
▪ H2.1 CofPs are composed of horizontal power structures (Kerno 2008; Wenger 2010). ▪ H2.2 CofPs are composed of vertical hierarchical structures, and those at the top control and influence the community and its resources (Davies 2005; Silva, Goel & Mousavidin 2009). ▪ H2.3 CofPs may have top-down hierarchical structures, but all legitimate members can potentially control/influence the community and its resources (Moore 2006). ▪ H2.4 The conceptualisations of the relationship between power and hierarchy in H2.1 – H2.3 are too simplistic.
In the next chapter, I outline the methodology used to investigate these hypotheses and describe in more detail my conceptualisation of power, hierarchy, and status in the Popheads CofP.
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3 Chapter 3: Methodology
Introduction
Chapter 3 chapter outlines the methodology used in this research. In Sections 3.2 and 3.3, I begin by outlining the data selection and collection processes involved. Section 3.4, which comprises the main body of this chapter, then discusses the methods used to analyse the data. Specifically, I outline how I chose the four linguistic forms explored, describe how power, status, and hierarchy are defined and measured, and explain the ethnographic component of my analysis. Section 3.3 continues with a discussion of the methods used to explore the four research questions analysed in this work. Finally, I discuss the methodological limitations of my approach, reflect on the ethics, and describe the data presentation strategies I employ in my analysis.
Data selection
This research explores the relationship between power, status, and hierarchy through an exploration of the control and negotiation of linguistic forms subject to endogenous LCM policies. Therefore, one of the key decisions in the research process involved identifying a linguistically creative online CofP which would allow for the exploration of the research questions considered here. I narrowed down the scope early on and decided to focus on a community hosted on the platform Reddit for several reasons. Firstly, Reddit is recognised as an "ideal environment for research on language change" because of the dynamic and diverse nature of the site (Stewart & Eisenstein 2018: 2; see also Kershaw, Rowe & Stacey 2016). Secondly, as will be discussed in the exploration of the platform in Section 4.2, Reddit consists of a series of interest-led communities known as subreddits. Therefore, unlike, for example, Tumblr and Twitter, where the boundaries of a community are often hard to delineate as the sites consist of a series of blogs (see Hillman, Procyk & Neustaedter 2014: 4), it is comparatively easy to determine what is community content and who is a member of a given community (Robards 2018). Finally, a timestamped corpus of almost all posts made to Reddit from the origins of the platform in 2005 to what was then present-day (June 2018) was already publicly available and easy to access (Baumgartner 2019).
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Initially, I observed five linguistically creative Reddit-based communities (which are known as 'subreddits') over a period of four weeks. At the end of this time, I decided to focus on Popheads, a community dedicated to the joint enterprise of discussing, reviewing, rating, and promoting mainstream pop music and artists (see Section 4 for a comprehensive overview of the community). This decision was primarily made because Popheads was the community that most clearly met all of the criteria to be classified as a CofP (as I will argue in Section 4.8). Additionally, the community had been in existence for 34 months at the time of data collection, meaning that data was plentiful and it would be possible to undertake longitudinal analyses on the language patterns discovered. Finally, although I had not engaged with the community before undertaking the study, as a fan of mainstream pop music, I had a personal interest in the practices of the community and felt that I shared a reasonable degree of knowledge with members.
Data collection
To source my data, I first downloaded the full Reddit corpus (Baumgartner 2019) which, at the time of access, contained every available submission and comment (that is, ones which had not been deleted prior to data collection) made to Reddit between December 2005 and May 2018. The data was collected on a rolling basis by the corpus creator approximately one month after it was posted to the platform. I then created the Popheads subcorpus by copying only posts which originated from the Popheads community to a new directory using a Bash script. The data was subsequently cleaned using two Perl scripts that I had written to remove unnecessary HTML coding and to transform the Unix timestamps used in the corpus to human-readable timestamps. In total, the final Popheads corpus is comprised of all available 1,097,756 posts made between 22nd August 2015 (the day of the community's inception) and 31st May 2018. Of these posts, 48,752 are submissions (posts which start a new thread in the community and set the agenda for the rest of the discussion) and 1,049,004 are comments (posts which are replying to a submission or another comment within a submission post). There are 32,341,609 million tokens in the corpus, of which 157,323 are unique. Finally, the corpus contains contributions from at least 25,549 members (posts from accounts deleted prior to data collection are marked with a [deleted] tag instead of the original author's name, so it is not possible to trace the exact number of contributors). Each post in the corpus is also
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accompanied by metadata including the timestamp of the comment, the author's (online) name, and a unique ID code which can be used to determine how many replies the post received.
Data analysis
The research questions explored in this thesis are investigated through an in-depth exploration of the emergence and (where applicable) the banning of four linguistic innovations. This section first discusses how the four innovations were identified and selected for further analysis. I then explain how status, power, and hierarchy are defined and measured in my research, before discussing the ethnographic component of this work. Finally, I outline the specific methods used to answer each of my research questions.
Linguistic forms for analysis
In selecting linguistic forms to examine in the case studies that comprise this thesis, it was important that they were:
a) Demonstrably significant to community members and the community's shared linguistic repertoire. b) Subject to an LCM policy at some point during the data collection period to allow for the investigation of the hypotheses relating to the control of linguistic resources. c) Introduced during the data collection period (as opposed to having been in use from the beginning of the community) to enable the exploration of the hypotheses relating to the weak-tie theory of language change and the role of innovators and early adopters in an online CofP.
To find forms which met criteria (a), I first used a keyword search to identify metalinguistic discussions about the community's lexicon which occurred organically between Popheads' members during the data collection period. I then collated a list of the twenty-five forms which were identified as frequently occurring, salient, or important to the community by at least two Popheads members.
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These twenty-five forms were then cross-referenced with the list of forms which had ever been banned under the community's LCM policy, and this left four terms: buy x on iTunes (a way of linguistically performing the identity of being a fan of x, with x almost always being a song or album), delete it fat ('I dislike/disagree with your opinion'), wig ('surprised'/'impressed'), and tea ('gossip'/'truth'). Finally, I mapped the frequency of these forms over time and verified that they were introduced to the community during the data collection period and thus met criteria (c). Further investigation revealed that tea was not included on the community's LCM policy until July 2018 (two months after the end of the data collection period) and thus could not be used to investigate the control of linguistic resources in the community. Nevertheless, the form was retained both because of its salience to the community and also to ensure I had enough data to investigate the weak-tie theory component of the research. This decision means that there are four case studies in total, but only three are interested in power, status, and the control of linguistic resources through processes of LCM. Importantly, before any analysis took place, the concordance lines for each of these four forms (and their variant spellings) were carefully examined, and any lines which did not match the innovative sense considered in this research were removed from further analysis. This included, for instance, lines where the sense of tea referred to a literal cup of tea, rather than the 'gossip'/'truth' sense of interest in this study. Also separated at this stage were lines where the innovative sense was simply being mentioned (for instance, in a quotation) as opposed to being used directly:
Direct usage:
(1)
Mentions:
(2)
2 When quotations from the corpus are presented in this work, they are reproduced alongside the pseudonyms assigned to each member, the timestamp of the quote (in the format DD/MM/YYYY HH:MM), and the score that each post received (which is presented after the timestamp). Posts from users who were members of the moderating team at the time will be marked with an [M] next to the pseudonym. 48
(3)
Lines in which the form is only mentioned, such as those exemplified in (2) and (3) above, were excluded from all further quantitative analysis and are not considered when I discuss diffusion or usage. Nevertheless, many of these mentions, as will be apparent in the case studies, proved valuable when discursively exploring LCM in the community.
Defining power, status, and hierarchy
Three concepts which are critical to this thesis are power, status, and hierarchy. Power and status are sometimes used synonymously across the literature to refer to the same phenomenon (Spencer-Oatey 1996); however, here, there is a substantial difference in usage. Scholars have identified two key issues relating to studies concerning power. Firstly, power is sometimes treated as a self-explanatory concept and is not suitably defined by the researchers (see Kucherenko 2016 for an overview of this issue in linguistic research). Secondly, power is often treated as something negative, corruptive, controlling, subjugating, or even abusive (Dunbar 2015; Turner 2005; Wetzel 1993). Consequently, it is necessary to begin with a definition which is clear, appropriate, and recognises that power is fundamental for social cohesion (Turner 2005: 18) and not an inherently negative phenomenon. Thus, power is defined here as the ability to consciously or unconsciously control or influence other people's behaviour in a specific social context. Influence, in turn, is defined as the ability to knowingly or unknowingly maintain or alter the behaviour of another person. Control is the ability to knowingly maintain or alter the behaviour of another person, typically by coercion or under threat of punishment. Meanwhile, status is defined as a series of (mostly) quantitative measures of an individual's behaviour in the community. Status is measured in nine ways (which will be discussed in-depth below): 'comments contributed', 'submissions contributed', 'replies received', 'one-link ties formed', 'ten-link ties formed', 'months active', 'months remaining', 'median score received', and the binary variable of 'moderator status'. To investigate the possibility, suggested by some of the CofP literature (Mak & Chui 2013; Wilson 2009), that status, hierarchy, and power may be more complex and multidimensional than is broadly recognised, each status measure is envisioned as a possible hierarchy in the community. So, for instance, there is a possible hierarchy of 'comments
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contributed', with the most prolific commenters being at the top and the least prolific at the bottom. In this way, the starting point for this research represents a departure from those theories that talk of a single hierarchy of power in a CofP (Davies 2005; Moore 2006; Silva, Goel, and Mousavidin 2009). This research assumes that there may be multiple hierarchies, with each hierarchy potentially having a different relationship to power in the community. Additionally, as discussed in Section 2.6.4, Eckert & Wenger (2005) demonstrate that hierarchical positions do not always correlate with degrees of power in CofPs. Therefore, in this research, I do not automatically equate hierarchy with power. That is, I do not assume that because someone scores highly on a status marker, and is thus placed at the top of a community hierarchy, they will have the ability to influence or control other members. In summary, power is the ability to control or influence others in certain social contexts, status is a member's location in the hierarchy or hierarchies of the community (which is approximated by a series of mostly quantifiable measures), and a member's positions in the hierarchies are not automatically assumed to be synonymous with their degree of power in the community.
Measuring status
When considering status, it was important to ensure that the measures reflected the potentially complex nature of status in an online community. Therefore, I decided not to combine all of the markers of status into one measure but to explore them separately. This method has a precedent in sociolinguistics. Labov (2001), for instance, measured network centrality and tie strength using five interrelated variables he called 'communication indices'. Each communication index looked at a different measure, including how many neighbours an individual encountered regularly, how many of their friends lived on their block, and how many lived in the wider neighbourhood. This method of exploring individual measures led to findings that advanced knowledge relating to sound change and SNA, which might have been missed if all of the variables had been grouped into one network score. Traditionally, when exploring community social network variables, most sociolinguistic studies have taken a snapshot of the network at one point in time and have treated the dynamics within the network as static. However, there is a growing trend, led by computer scientists (see Ahmad & Teredesai 2006), to acknowledge that communities (and individuals' roles in the communities) are dynamic. Moreover, it is a fundamental principle of
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the CofP framework that practices and membership are constantly in negotiation (Wenger 1998), so a static approach would potentially be problematic when investigating a CofP. To exemplify, using a static approach, if this research concluded that
the infrequent or one-time poster has contributed little time and energy to the group and has made a relatively small impact on the group as a whole. This person is therefore less likely to have gained any reputation at all, much less one of prestige, and can therefore have only a marginal role (Golder & Donath 2004: 6).
Consequently, this work distinguishes between 'active members' and 'full members'. Any person who contributes to the community can be considered an active member (specifically they are considered active from the month of their first post to the month of their last post). Where possible, in this research, I have tried to adopt an emic approach (Harris 1976; Jardine 2016) and incorporate Popheads members' own ideas and definitions about how their community works into the methodology. Therefore, I have taken the lead for defining full 51
members from how Popheads members themselves define them. Specifically, in Popheads, users are forbidden by the community rules from posting and promoting their own music in the community, unless they are 'established members of the community'. The moderators define established members as those who have made "at least 10 posts/comments spread out over a few months on the subreddit" (
Status marker 1: Moderator status Moderator status is a binary variable. At any one time, there are approximately 9-12 officially-appointed Popheads members who have the status of 'moderators' in the community. Moderators are the only Popheads members who have any official degree of power in the community. Specifically, they have unique privileges, such as the ability to create rules for the community, delete posts, ban other members, and promote others to the role of moderators (so only they control who is granted official power).
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In his discussion of membership on Reddit, Robards (2018: 193) writes that, in the Reddit hierarchy, moderators appear above any other member of a community, and he refers to moderators as "the ultimate authority" in a Reddit community. Similarly, Kendall (2008: 497), in a study of an online CofP, concluded that "moderators' words on the site carry more weight", adding that moderators have "considerable power over others' contributions to the site" (Kendall 2008: 497). Thus, if one were taking a unidimensional view of power, it might be logical to assume that moderators would be at the top of the hierarchy of the Popheads community and they could influence and control the linguistic resources of the community.
Status marker 2: Number of months active in the community ('months active') Several research studies of online communities have found that established or long-term members are better able to influence the behaviour of other users (Kanters 2017; Paechter 2006; Silva et al. 2009; Stommel & Koole 2010). Therefore, the second status marker is a measure of how many months a user has been active in the community. A user is counted as active once they have made at least one post (that is, a submission or comment) to the community.
Status marker 3: Number of months remaining in the community ('months remaining') The third status marker is the number of months a user remains active in the community after a specified point (such as the point of early adoption, for instance). A user is considered inactive from the start of the month after their last ever post in the community. 'Months remaining' was not a measure investigated in previous literature on status. However, the number of months that a member remains active in the community can be used to approximate if they were on an inbound or outbound trajectory (Wenger 1998: 154-155) in the CofP at a given point in time. If a user has a low score for 'months remaining', they are likely on an outbound trajectory (that is, nearing the end of their time as a member) and can be assumed to have lower levels of affinity with the community. In contrast, users who score highly for 'months remaining' are assumed to be engaged members, with high levels of affinity, who are on inbound trajectories in the community.
Status marker 4: Number of submissions contributed relative to months active in the community ('submissions contributed')
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Research has found that individuals identified as high-status members of online communities are more likely to contribute directly to the community's practices and activities by, for instance, extending the knowledge bank of the community (Faraj, Kudaravalli, & Wasko 2015; Yoo and Alavi 2004). My ethnographic observations of the Popheads community suggested that the best way to measure the extent of members' contributions is via the number of submissions they post. A submission is a post that starts a new 'thread' in the community, and thus typically either introduces new content into the community or sets the agenda for the subsequent discussion. To ensure that this measure did not privilege members who had been active for longer in the community, it was calculated by dividing a users' cumulative number of submissions by the overall number of months that they had been active.
Status marker 5: Number of comments contributed relative to months active in the community ('comments contributed') Research has consistently found a relationship between regular or prolific posting activity and status in online communities (Huffaker 2010; Kendall 2008; Paechter 2006; Robards 2018; Silva, Goel, & Mousavidin 2009; Stommel & Koole 2010; Yoo & Alavi 2004). Therefore, the fifth status marker explored in this research is 'number of comments contributed'. A comment is created when a user replies either to a submission or to another comment within a submission. Typically, then, comments are associated with discussion and interaction (as opposed to contributing new content or agenda-setting). This measure is calculated by dividing the cumulative number of comments for each user by the number of months that they had been active in the community.
Status marker 6: Number of replies received relative to the number of posts contributed ('replies received') The number of replies a user receives to their posts is treated as a status marker in the literature (Belak, Lam & Hayes 2012; Bruns & Burgess 2011; Burke et al. 2007). Burke et al. (2007: 2), for instance, argue that the receiving of replies indicates that the community "believes the author is a valuable member worth its attention". In Popheads, a member receives a reply when another user responds directly to either one of their comments or submissions. To ensure that prolific contributors are not overly favoured, this measure is calculated by dividing a member's cumulative number of received replies by the overall number of posts that they have contributed. 54
Status marker 7: Number of one-link ties formed relative to the number of posts contributed ('one-link ties formed') Huffaker's (2010) research concluded that leaders of online communities are more likely to build reciprocal relationships with other members (that is, they reply to people who reply to them). In this research, if
Status marker 8: Number of ten-link ties formed relative to the number of posts contributed ('ten-link ties formed') This measure is similar to 'one-link ties formed' (defined above). However, for a ten-link tie to have formed, two users must have replied to each other's posts at least ten times. This measure considers the number of relationships a user has formed that are defined by mutual and sustained interaction. In SNA terms, this marker is approximately equivalent to the 'number of strong ties formed'. This measure is calculated by dividing a user's raw number of ten-link ties formed by the overall number of posts they have contributed.
Status marker 9: Median score received on posts contributed ('median score received') Kanters (2017) and Johnson, Faraj, & Kudaravalli (2014: 798), in their Reddit-based research, note the link between status and receiving high scores on posts. Indeed, on Reddit, and thus Popheads, members can "upvote" or "downvote" each other's posts to indicate content they, respectively, appreciate and do not appreciate. Reddit then provides an overall "score" for each post which broadly reflects the overall number of upvotes and downvotes it has received. Initially, I intended to calculative the cumulative score that Popheads users had received on all of their posts. However, following Jaech et al.'s (2015) discussion regarding how extremely high scores on one or two posts can bias the cumulative measure, I decided instead to determine, for each user, the median score they had received across the posts that they had contributed.
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However, there is another potential issue with this measure that I could not control for. Specifically, on Reddit, an algorithm is used which, by default, tends to show posts with high scores near the top of the page. This means that both submissions and comments with high scores are afforded more opportunities than 'typical' posts to be seen and upvoted by other members.
Although there are nine status markers investigated as variables in this work, only one of these (moderator status) is an officially recognised mark of status in the community. Individuals who score highly on the rest of these measures have no officially sanctioned status. However, I hypothesise that they may have a degree of status reminiscent of Bourdieu's concept of symbolic capital, which refers to an individual's "degree of accumulated prestige, celebrity or honour" (1993: 7) within a specific cultural context. To summarise my approach to the study of power, status, and hierarchy in this study. Power is the ability to control or influence others in certain social situations. Meanwhile, status is a series of one binary and eight quantifiable measures of where members sit in the hierarchies of the community. Finally, a member's positions in the hierarchies are not assumed to correlate with their degree of power in the community.
Ethnography
A key part of my methodology in this research involved online ethnographic observation (Androutsopoulos 2008; Danet 2001; Gillen 2018; Pink et al. 2016) of the Popheads community. This process primarily occurred over twelve months between June 2018 and June 2019. As the time of my ethnographic observations post-dated the end of the data collection period (May 2018), I focused most of my time on reading and analysing retrospective posts from the time covered in my corpus, as opposed to present-day contributions. My observations consisted of reading posts by community members in order to understand the CofP, the language and cultural references used, and also the dynamics between members. This was important in allowing me to identify the discursive practices of the community and how discourses relating to power and control manifest. Given the size of the corpus, I could not read all the data (although I estimate that I read around 90% of the posts during the research process); therefore, I used keyword searches to guide my reading.
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Specifically, I looked at every thread which contained the four innovative forms of interest to this research and also every thread containing keywords relating to power and the control of linguistic resources (including 'banned', 'censorship', 'moderators', and 'rules'). After six months of observing the community, I began to participate in some of the key community practices, including 'rates' (a practice discussed in the next chapter) and recommending music in response to queries from other members. My participation was driven both by my interest in the subject matter and an academic desire to confirm that I had understood the practices, joint enterprise, and shared repertoire of the CofP.
The weak-tie theory of language change: innovators
The first research question explored in this thesis concerns the applicability of the weak-tie theory of language change's prediction about the innovators of language change to an online CofP. Specifically, the theory predicts that the innovators will be peripheral members of a community with weak-tie links to other members. In offline studies, peripheral (or weak-tie) members of a community are typically identified as those who have few multiplex relationships with others (Bax 2000; Milroy & Llamas 2013). In other words, weak-tie members are those who do not fulfil multiple social roles or functions for other members of the community. For instance, the people with the strongest ties in the Milroys' Belfast study were those that lived in the same geographical area as their extended family members, who were employed in the same workplace as their neighbours, and who associated with their workmates and other members of their neighbourhood in their spare time (Milroy & Milroy 1985). In contrast, peripheral or weak- tie members did not typically fulfil multiple socials roles and functions for other members. However, the multiplex criterion is not straightforwardly adaptable to online communities. Therefore, I approached this study with a broader understanding, informed by my ethnographic observations, of what it means to be a peripheral member of the Popheads community. Specifically, to be a peripheral member is to post infrequently, to be relatively unengaged, to show little commitment, and to interact infrequently with other members. To operationalise these criteria, I defined peripheral members as those who consistently scored lower than the community median across multiple markers of status in the community. Specifically, I calculated the monthly community median values for each status marker to serve as a baseline (as, for instance, it is not possible to know if a person's score for 'replies
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received' is low unless we know what a 'typical' number of replies received in the community at that point in time is). However, because of the large number of peripheral members who rarely contribute to the community (see Section 4.4), a threshold was set to ensure that only full members are included in these community median calculations. As described above, full members must have posted at least ten times over a minimum of two months. An innovator will be regarded as having a low status for a measure, if, in the month that they became an innovator, they scored lower for that measure than the monthly community median value. To be regarded as a peripheral member of the community, a user must score lower than the community median across at least four of the eight quantitative status markers. Finally, when discussing innovators in sociolinguistic contexts, it is important to clarify if an individual can be considered an 'innovator' if they were the first person to introduce a form into a community but they were not the person who invented the form. In the context of the current research, all of the forms studied were in usage on other social media platforms (such as Twitter) prior to their first usage by a Popheads member. A literal interpretation of the word 'innovator', then, would lead us to conclude that the 'true' innovators exist outside of the Popheads community and we cannot label the first person who used a word on Popheads as an innovator. However, Labov (2001: 362) distinguishes between two types of innovator: the first who uses "a given linguistic form for the first time" and the second who "introduces a form used by one group to another group". The latter definition seems to conform to Milroy & Milroy's (1985) understanding of what it means to be an innovator in their SNA research (in which they, for instance, talk about "further innovators" who transmit an innovation from one community to another). Therefore, Labov and the Milroys' use of the term would suggest that referring to the person who introduces a pre-existing emerging form into the Popheads community as an 'innovator' is unproblematic.
The weak-tie theory of language change: early adopters
The Milroys (1985: 367), in their seminal work on sociolinguistic social network analysis, wrote that after the early adopters have taken up a form, the "innovation is typically disseminated from the inside outwards with increasing speed, showing an S-curve of adopter distribution". I interpreted this to mean that the end of the early adoption period would be marked by a noticeable uptake in new users, which would be observable by plotting the cumulative number of users over time on a graph and looking for the sharp increase which
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characterises the start of an S-curve. Therefore, this is the method that was used to identify the end of the early adoption periods for the forms studied here (and thus also to determine the sample of early adopters studied). To clarify, then, the early adopters are the people who take up the innovation after its usage by the innovator and before the sharp increase in new users indicating the start of widespread diffusion. An argument could be made that this approach was somewhat subjective. However, based on my ethnographic observations of the community, and the absence of any other existing methodology for identifying the end of the early adoption period when looking at ongoing lexical changes that are unlikely ever to reach full completion, I concluded that the method was sound. The second research question explored here asks if the weak-tie theory of language change's prediction that early adopters will be central leaders in their community holds in an online CofP. I operationalised the classic concept of 'centrality' or 'leadership' as scores across multiple status markers at the time of early adoption which were higher than the community median. Specifically, I investigated what percentage of early adopters fell above, below, or in line with the community medians across the eight quantitative status markers of interest. If the majority (over 55%) of early adopters scored higher than the community median (calculated as discussed above) at the time of uptake for the marker, then it is considered to be a marker associated with early adoption. I also investigated what percentage of the moderating team active during the early adoption period took up the forms of interest and served as early adopters. For moderator status to be a variable associated with early adoption, I required that 55% or more of the moderating team must have been early adopters. The method described above was a rather simple but effective way of achieving an overall picture of the status of the early adopters, especially as it was complemented by the more fine-grained statistical analysis associated with the third research question. However, it is important to note when considering this part of the analysis that I am not claiming that these markers are significant predictors of early adopter status or claiming to have found differences between early adopters and non-adopters. Rather, I am looking solely at the early adopters and where they seem to sit in the status hierarchy/hierarchies of the community. Another factor to consider is that the hypothesis associated with this research question, 'members with high status will be the early adopters of linguistic forms', operates within a monodimensional view of status inspired by the existing research in the sociolinguistic SNA paradigm. Nevertheless, this research remains open to the idea that status may be complex
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and multidimensional and thus also open to the idea that the hypothesis may prove to be too simplistic when the findings are reviewed. The third research question explored in this work interrogates which (if any) of the status markers are statistically significant predictors of early adopter status. In contrast to the relatively simplistic quantitative analysis employed above, here, I employ principal component analysis (PCA) and logistic regression analysis to better understand the potentially complex and multidimensional nature of the relationship between early adoption and status. In this analysis, the status markers of the early adopters of a form are compared to the status markers of the full members who were active in the CofP during the early adoption period (and who thus could have been early adopters) but who did not adopt the form. The decision was made to focus only on full members as, in a pilot study, the very high number of active members with extremely low scores across most status markers compromised the validity of the statistical analysis. When creating the datasets used in the PCA, the status markers for the early adopters were taken as a snapshot in the month they took up the form. However, the situation was more complicated for the non-adopters. All full members who did not adopt during the period, despite having had the opportunity to, needed to be included in the analysis. However, if the early adoption period lasted 12 months, the problem becomes at which point during these 12 months to take a snapshot of the status markers of non-adopters to use in the statistical analysis. I was unable to determine a perfect solution to this dilemma, so I proceeded with the least problematic method possible. Specifically, for all non-adopters who were still active at the end of the early adoption period, the snapshot of their status markers in the last month of the early adoption period was used (the reasoning being that this was the last possible point of early adoption for them, and if they had not become an early adopter by this point, they never would). For all the non-adopters who had left the community during the period of early adoption, their status markers in the month they that they left the community (that is, the last possible time of early adoption for them) were used instead. Before undertaking any of the more complex statistical procedures, I first performed a Spearman's rank-order correlation coefficient test using the cor function of the programming language R to determine if there were any strong correlations between the status markers considered in this research. Strong correlations could potentially problematise the findings as I would be examining two variables which capture the same marker of status. Spearman's rank correlation coefficient is a non-parametric test (that is, it does not assume the data will 60
be normally distributed) which measures the strength of the relationships between the inputted variables (Franzese & Iuliano 2019; Sedgwick 2014). Moreover, in comparison to other correlation tests, Spearman's rank is relatively unlikely to be negatively affected by outliers (Franzese & Iuliano 2019: 720). For each possible correlation, a Spearman correlation coefficient value was returned: a value of +1 indicates a perfect positive correlation, a value of 0 indicates no correlation at all, while a value of -1 indicates a perfect negative correlation between the two variables. It is generally accepted (Dancey & Reidy 2017: 182; Ratner 2009: 140) that a value between 0.7 and 1 (or between -0.7 and -1) indicates a strong correlation between two variables. Therefore, any correlation values between -0.7 and 0.7 will be accepted as unproblematic. This research proceeds on the presupposition that power may be a multidimensional concept that cannot be easily reduced to a single hierarchy. Therefore, following the correlation test, principal component analysis (PCA) was performed using the prcomp function of R. PCA is a multivariate technique which transforms big datasets containing information on multiple variables into more simplified versions that make the data easier to interpret (Abdi & Williams 2010; Shlens 2014). Specifically, the PCA analysis transforms the existing variables (e.g. comments contributed, replies received etc.) into new variables (or 'principal components') which retain most of the key information (or 'variability') from the dataset. Some principal components (PCs) may be much more representative of the original dataset than others, and the importance of each PC can be determined by looking at the 'proportion of variance' that it accounts for. By default, this research will closely consider the two PCs which account for the highest proportion of variance in the dataset. However, I will also examine any additional PCs which account for 5% or more of the information in the dataset. To determine the relationships between the original inputted variables and the new PCs, it is necessary to examine the 'loadings', which list the extent to which each of the original variables is represented in each of the new principal components. The other key part of PCA of interest was the early adopters and non-adopters' scores on the new PCs, information that is represented, in this research, on PCA plots which allow for the visual representation of the hypothesised relationship (and any interactions) between the PC variables. Following the PCA, I used the glm function of R to perform a logistic regression analysis to determine if any of the PCs of interest are statistically significant predictors of early adopter status (which serves as the binary response/dependent variable) in the Popheads 61
community. Finally, to check the performance of the logistic regression models computed, I used the R2 function (belonging to the 'performance' library) of R to perform Tjur's R2 tests on the models. Tjur's R2, which is also known as the coefficient of discrimination, assesses the predictability of a logistic regression model (Tjur 2009). A score closer to 1 indicates that the model has excellent levels of predictability, while a score close to 0 indicates that the model has poor levels of predictability.
Power, control, and linguistic content moderation
In order to answer the fourth research question ('Who has the power to control or influence linguistic resources in the Popheads CofP?'), I identified and explored three different stages in the LCM process which intersected with power and control. The first stage is the advocation for LCM, the second concerns the implementation of LCM policies, and the third centres on the effectiveness of LCM. To explore these three stages, I took inspiration from Computer-Mediated Discourse Analysis, also known as CMDA (Herring 2004; Herring 2010). The CMDA framework allows researchers working with online data to "identify and describe online phenomena in culturally meaningful terms, while at the same time grounding [their] distinctions in empirically observable behavior" (Herring 2004: 338). Specifically, the framework advocates for the use of a range of qualitative and quantitative discourse analytic methods combined with "paradigm-independent best practices" (Herring 2010: 237). In the analysis concerning research question four, then, I draw, simultaneously, on insights gained during my ethnographic observations of the CofP, various discourse analytic methods, and quantitative analysis of the status markers for the members of interest.
Limitations
Before moving onto explore the findings of this research, it is necessary to consider the methodological limitations that have not been discussed above. Firstly, by studying only status markers, I am effectively ignoring many crucial social variables which have been found to be highly significant in the sociolinguistic study of language change and variation. Indeed, in offline sociolinguistic studies, SNA variables, similar to those studied here, were introduced into the discipline to complement, rather than
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replace, traditional variables such as age, gender, and social class. For instance, the Milroys (1985), Labov (2001), Dubois & Horvath (1998) and Eckert (2000) all found correlations between linguistic variables, gender, and SNA variables (or the equivalent thereof). In an ideal world then, the current research would also consider age, gender, race, social class, geographical location, and, in line with third-wave sociolinguistics (Eckert 2012; Eckert 2018), stylistic and identity variables. However, the anonymity afforded to members of Reddit communities, and the associated lack of demographic information available on the site, means that without extensive surveying of all of the thousands of members of the Popheads community, I would not be able to gather data on these variables. Additionally, this work does not control for linguistic variables which have been found to be influential in the study of variationist sociolinguistics (Cacoullos & Walker 2009; Ito & Tagliamonte 2003; Tagliamonte 2011). Labov (2001) cites Le Page and Tabouret-Keller (1985) who write that social networks "are a more satisfactory alternative to [...] social or economic or other groups" (Le Page and Tabouret-Keller 1985: 186). However, Labov (2001: 326–328) is critical of their argument, instead making the case that social network data is most significant when considered alongside variables such as age, gender, social class, and ethnicity. Nevertheless, in the same argument, Labov does concede that if one could hypothetically record all of the speech interactions of a community of one million people, then "such a massive data base might allow us to model the speech community through the mechanics of interaction alone with no reference to education, income, occupation, ethnicity […]" (2001: 326). He goes on to dismiss the idea, noting that the "best network studies" can only realistically focus "on one or two isolated groups of a dozen speakers or so" (326). However, one of the key advantages of studying an online social network such as the Popheads community is that one has access to timestamped logs of all of the public interactions between community members from the community's inception to the time of data collection. Every single innovator and early adopter in the community can be identified, and extensive metadata about their activities in the community can be studied, something which is almost impossible in an offline study. Although, in real-world studies, for time and practical reasons, as Labov writes, it is the case that researchers can only focus their efforts on small networks, in an online context, the availability and ease-of-access to data allow one to take a first step in creating Labov's hypothetical "massive data base [which] might allow us to model the speech community through the mechanics of interaction alone" (Labov 2001: 326). This constitutes a distinct and unique advantage of online research. In other words, then, it is not ideal that this research 63
was conducted in the absence of crucial social data about the members discussed, and any future research on status in online CofPs should endeavour to correct this by incorporating a method to collect participant's demographic data into the research design. However, the fact that I am working with a full corpus of every interaction between members of the community over a two-and-a-half-year period will hopefully go some way towards compensating for this methodological shortcoming. Secondly, although, as discussed above, I have spent extensive time observing the Popheads community and consider myself to have an excellent understanding of the community and its practices, I am nevertheless still mostly an outsider who is analysing data and imposing meaning and intentions on retrospective conversations. There is, then, a possibility that my analysis may not be framed in a way that aligns with Popheads members' understanding of the way their community works and their discursive practices. The solution to this dilemma would be to contact participants and discuss what their intentions were when creating their posts. However, even if this was possible from a practical point of view (given the time and resources this would necessitate), Carter (2004: 177) notes that "even participants' own accounts of intentions and responses fall foul of a circular dialectic of relativity and the difficulties of interpreting intentions". Indeed, asking individuals to recall what they intended in an informal online conversation that may have taken place three years previously is not necessarily an unproblematic way of analysing community interactions. The issue described above is, of course, not unique to this research and impacts a great deal of the work in the discourse analysis tradition. Therefore, it is not a massively problematic flaw, but it is something to bear in mind when considering the analysis presented in this thesis.
Ethics
Currently, there are no universally accepted ethical guidelines for conducting research using online data (Rambukkana 2019; Tiidenberg 2018). For example, the Association of Internet Researchers emphasise "the value of a casuistic or case-based approach" when considering the ethics of studying online data (Markham & Buchanan 2012: 7). As all data used in this research is publicly available and posted by authors who are evidently using online pseudonyms, The University of Manchester's Ethics Oversight Committee declared that this work did not require ethical approval or consent to be obtained from individual contributors. Nevertheless, to safeguard their digital anonymity, community
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members discussed here will be referred to by pseudonyms generated using the SpinXO (2020) random name generator.
Data presentation
When quotations from the corpus are presented in this work, they are reproduced alongside the pseudonyms assigned to each member, the timestamp of the quote (in the format DD/MM/YYYY HH:MM), and the score that each post received (which will be presented after the timestamp). Posts from users who were members of the moderating team at the time are marked with a [M] next to the pseudonym. All passages from the Popheads corpus used in this thesis have been rendered as they appear in the corpus (except where clearly indicated otherwise), so any instances of non- standard lexis or grammar in quoted passages can be assumed to have been reproduced from the original text. Where necessary, I gloss non-standard lexis or uncommon abbreviations in square brackets. In most cases, the gender of participants is unknown. However, I will demonstrate in the next chapter that a large percentage of members of the community self-identify as male, so male pronouns will be used to refer to participants throughout when discussing members whose self-reported gender is not known to myself.
Conclusion
To summarise, this chapter described the processes of data selection and collection used in this research, before proving an in-depth overview of the various data analysis methods employed. I then considered the limitations and ethics of this work and finished by outlining the data presentation conventions followed. The next five chapters now present the findings of this research, beginning first with my ethnographic overview of the Popheads community and then proceeding to consider the four research questions that comprise this study through in-depth explorations of the emergence, diffusion, and banning of four linguistic forms.
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4 Chapter 4: The Popheads Community of Practice
Introduction
Chapter 4 provides a thorough ethnographic analysis of the Popheads community and serves as crucial context for the linguistic analysis in the succeeding chapters. I first provide an overview of Reddit, the platform on which Popheads is hosted. I then introduce the Popheads community, focusing specifically on its conventions, size, and demographics (with the latter information being derived from the results of pre-existing self-reported survey data). Finally, I draw on both my ethnographic observations and textual discourse analysis of posts from the Popheads corpus to build the argument for Popheads being a CofP.
Reddit is an extremely popular aggregation and discussion site with over 430,000,000 monthly active users (Reddit 2020a). At the time of writing, in June 2020, Reddit is ranked by the web traffic analysis company Alexa (2020) as the eighteenth most visited website in the world (and sixth most visited in the US). Reddit's information page states that:
"Reddit is home to thousands of communities, endless conversation, and authentic human connection. Whether you're into breaking news, sports, TV fan theories, or a never-ending stream of the internet's cutest animals, there's a community on Reddit for you" (Reddit 2020a: n.p.).
Indeed, Reddit is composed of over 130,000 individual and highly diverse communities known as 'subreddits'. Any Reddit member can create a subreddit, and, typically, each subreddit has a designated theme, topic, or specific purpose, which vary from the serious to the comical. For instance, there is a subreddit for sharing knowledge about urban farming and gardening (r/UrbanGardening), one where members discuss examples of LGBT+ erasure in
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academia (r/SapphoAndHerFriend), and one dedicated to sharing pictures of cats standing up on their hind legs (r/CatsStandingUp).3 Each community has one or more moderators (typically the community creator and members they, or other moderators, promote to this position). Moderators can impose rules on the subreddit (in addition to the site-wide rules enforced by Reddit) and are free to ban users or delete posts made to the community. The vast majority of content moderation and regulation on Reddit is performed at the community-level by these volunteer moderators (Seering et al. 2019), and it is only in relatively exceptional circumstances that the administrators or 'admins' (Reddit employees who have duties site-wide) will intervene. Indeed, the Reddit administrators have been critically described as taking "an extremely hands-off approach" to moderating content on the site (Massanari 2017: 331). The community-orientated structure of Reddit means that the platform differs considerably from other popular social media sites such as Twitter and Instagram (Seering et al. 2019). On platforms such as Twitter and Instagram, a user signs up to the website and gets their own profile. They can then post content to their profile, and other users can choose to follow them to see their content. A user can build and cultivate their social networks by following people of interest, which will result in seeing their posts on their timeline. In contrast, when a user joins Reddit, they do not receive a profile to post content to per se, but rather the ability to post content to subreddits. And instead of curating one's social network based on the profiles of other individual users, one instead chooses to join subreddits of interest (although there is also an option to follow the content of individual users too). Content created on Reddit, then, is very much community-orientated. Thus, Reddit data is often used in linguistics and the broader social sciences/humanities to explore hypotheses relating to the structure or behaviour of online communities (Cole, Ghafurian & Reitter 2017; Cunha et al. 2019; Robards 2018). Some subreddits are restricted (meaning anyone can view the community but users need approval from the moderators to post) or private (meaning one must send a request to the moderators in order to be considered for membership and allowed to view or post content). However, most subreddits are open and can be viewed by all internet users. Nevertheless, one must create a site-wide account in order to post to a community or to interact with other members. Once a user has created a Reddit account, they can choose to
3 The names of subreddits are prefaced with r/ on reddit as a general – and technological – convention of the site. 67
'join' or subscribe to a community: this will mean that they see (typically the most popular) posts from that community on their homepage when they log-in to Reddit. Importantly, one can subscribe to a community without posting or interacting with that community. Alternatively, one can post in open communities without actually subscribing to the community. Users can post 'submissions' to a community. Each submission begins a new thread and sets the agenda for the rest of the discussion. Users can then comment on the submissions and also reply to other people's comments on submission posts. Subsequently, a popular submission post can potentially receive thousands of comments. Reddit is mostly a text-based platform: one can post images and videos, but they must be posted as links which direct the user to an external site. The platform itself does not support the embedding of images and videos into posts. Reddit functions on an upvoting and downvoting system (Van der Nagel 2013). Users can upvote submissions and comments they find to be high-quality content (the criteria for which will differ from community to community) and downvote content they find to be low- quality. Each submission and comment on the site has a score based approximately on the overall number of upvotes and downvotes it receives from other members. By default, each new post has a score of 1 and this number increases or decreases to reflect the downvotes/upvotes it receives. Posts which are heavily upvoted are more visible in that they are displayed either towards the top of the subreddit's community page or, in the case of comments, they are displayed at the top of the comment section (unless users change their default setting to see, for instance, most recent comments first). Meanwhile, posts which are heavily downvoted become less visible and occur towards the bottom of a page. Much of the research to date on Reddit has focused on the problematic elements associated with the site, such as subreddits which promote misogynistic discourses (Massanari 2017), racism (Verhaar 2016), and far-right ideologies (Gaudette 2019). Massanari (2017: 329) goes as far as to argue that Reddit's "design, algorithm, and platform politics implicitly support these kinds of [problematic and toxic] cultures". However, as noted by Robards (2018: 187), "like any social space, it has both positive and negative dimensions". In this research, I focus on arguably one of the more positive Reddit communities, r/Popheads.
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Overview of Popheads
Although Reddit itself and many individual subreddits have been the subject of extensive academic research, this is the first study to investigate data from the Popheads community (with the exception of my work in Donlan 2020, which is based on research conducted for this thesis). Popheads was created on Saturday 22nd August 2015 by Reddit user
(1)
This post has a score of 165 (in comparison, the median score across all posts in November 2017 was just 5) and there are no dissenting opinions in the comments, suggesting that the above is a reasonably accurate account of the community's origins. The Popheads community is now a popular platform for dedicated fans of pop music to engage in their fandom practices: members discuss, review, and rate new musical releases, engage in serious and critical discussions regarding issues facing the music industry, promote their favourite artists, and share relevant news and gossip. Popheads is unapologetic in its dedication to the often derided genre of mainstream pop music. The community is primarily interested in commercially successful artists that are highly popular among young people in English speaking countries, such as Taylor Swift, Lady Gaga, and Ariana Grande. However, many lesser-known artists are also relatively well- represented in the community. The moderators of the subreddit have in place a number of rules about what can be posted and when. For instance, Popheads does not allow submissions related to the promotion of songs which are over 30 days old, preferring to focus on 'fresh' music. Illegal content (such as 'leaked' music or links to illegal downloads) is also banned. Tabloid content, defined as "non-newsworthy drama, sensationalist content" (
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entirely; however, users can only post it in official gossip threads, which were once created bi-weekly but have recently been posted daily. Unlike several other subreddits which have been the focus of academic investigation (see Gaudette 2019; Massanari 2017; Robards 2018; Verhaar 2016), issues such as hate speech and personal attacks on other members are rare issues in the Popheads community. One of the Popheads rules is that members must "keep things civil" (
(2)
This view seems to be emblematic of many members' opinions of the Popheads community, as signalled by the high score (24 in a month where the median score across posts was 3), and, after two years of observing and occasionally participating in the community, it is one that I share. Popheads is largely a jovial community that it is welcoming of newcomers and established users alike. Although, as with the vast majority of sites of public online interaction, there are disagreements and instances of antisocial behaviour, the overall tone of the community is positive and respectful.
Size of the Popheads community
In terms of the number of Popheads subscribers (that is, people who have 'joined' the community but not necessarily contributed content), the community became popular very quickly. As illustrated in Figure 4.1, by the end of August, when the community had been in existence for just nine days, Popheads had a remarkable 2,370 subscribers. A year later, in August 2016, the community had 11,944 subscribers, a number which had more than doubled by August 2017 to 29,294. At the end of the data collection period in May 2018, the community had 47,436 subscribers.
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Numbermembers of 10000
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Total Subscribers Active Members Full Members
Figure 4.1: Graph showing the number of subscribers, active members, and full members of the Popheads community throughout the data collection period.
However, while the number of people who seem to be interested in the Popheads community is very high, the number of users who contribute to the site is, and always has been, relatively low.
8000
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Numbermembers of 2000
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Active Members Full Members
Figure 4.2: Graph showing the number of active members and full members of the Popheads community throughout the data collection period.
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In terms of active members (a member is defined as active from the time of their first post to their last post in the community), the number never rises above 6,791 (with this peak occurring in January 2018). The median number of active members in the community is 3,692.5. The numbers are even lower when one considers the number of full members (active members who had made ten posts or more over at least two months). The number of full members peaks in March 2018, at 3,128 users. However, the median monthly number of full members over the lifespan of the community is 1,265. Therefore, Popheads has a core userbase which is relatively small and intimate. However, there are then a large number of users who do not contribute content and are happy to be 'lurkers' or, to use a more neutral term championed by Crawford (2009) and Robards (2018: 189), 'listeners'. Moreover, the numbers above may underestimate the number of listeners, since they only record registered Reddit users who have subscribed to Popheads. There is no way of knowing how many unregistered users, or Reddit users who have not subscribed to Popheads, are interested in the community.
Demographic overview
Reddit (and thus Popheads) primarily operates on a pseudo-anonymous basis. When signing up for an account on the site, users are asked only for their email address, a password, and to create a unique username which they are told at the time of registration "is how other community members will see you" (Reddit 2020b: n.p.). Indeed, while a user can choose to add a profile image which will be visible if another user clicks on their profile or hovers over their username, typically it is just their username that is visible by default when posting in a community. Users can add a brief biographical profile in an 'about me' section but, again, this is only visible to others who choose to find out more about them by visiting their profile. In Popheads, members can have a 'flair' (or avatar) appear next to their usernames, but the choice of flair is limited to pictures of pop stars which have been approved by the moderators. In other words, unlike on Twitter or Facebook, for instance, where profile images which are displayed alongside every post or comment can (albeit sometimes problematically in the case of inaccurate or false images) often be used to make assumptions about the identity of one's interlocutors, the same cannot be said on Reddit. Moreover, the usernames
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chosen by Reddit users are almost always pseudonyms with no correspondence to plausible offline or 'real' names (Van der Nagel & Frith 2015). Helpfully, however, the Popheads community conduct (approximately) yearly censuses, in which members are invited to fill in an optional anonymous survey which asks for key demographic information (including age, gender, country of origin, etc.) as well as information more relevant to the community's practices (such as preferred ways of listening to music). The first census, which received 325 responses, was conducted between February and March 2016. This was very early in the community's lifespan (having only been established in August 2015), and it was sparked by the community reaching 4,000 subscribers. The second census was undertaken in April 2017 to celebrate the community reaching 20,000 subscribers, and it was completed by 1,005 members. The last census completed within the data collection period was in May 2018, when 1,630 members filled in the survey to mark 40,000 subscribers. The survey data then, which is summarised below, more or less spans the entirety of the data collection period. However, caution should be used when considering the findings of the censuses in relation to the linguistic data presented later in this dissertation. The censuses were open to all Popheads users, including those who do not contribute at all to the site. Indeed, in the 2018 census, for the first time, responders were asked about the extent of their participation in the community and 47.8% of responders indicating that they only 'lurked' in the community and did not post content themselves. Therefore, while the findings below do provide a general overview of the type of people who visit the Popheads community, they are not necessarily indicative of the demographics of the users discussed in this work who contribute to the community and its practices. Additionally, there are potentially the same issues as with any anonymous self-reported data at play here (that is, the possibility that users are, for whatever reason, providing inaccurate answers). Regardless, I argue that this survey data is nevertheless useful for understanding the social demographics of the Popheads community. Moreover, the demographics reported here are consistent with my expectations based on the cultural reference points, anecdotes, and terminology I have observed Popheads members use in the corpus.
Gender
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male
female
other/prefer not to say
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Percentage of users
Feb-16 Apr-17 Apr-18
Figure 4.3: Self-reported gender of Popheads users.
There is a large gender gap in the Popheads community, with far more responders identifying as male than female. This gender gap was most evident at the time of the first census when 80% of users identified as male. Nevertheless, this gap does begin to close throughout the lifespan of the community. While just 18% of participants identified as female in 2016, this had increased to 31% by the time of the final census in April 2018. A chi-square test (χ2 =24.22; d.f. = 1; N= 1955) finds that this increase is statistically significant at p < 0.0001. The male bias in the Popheads community may be, in part at least, due to the gender imbalance on the Reddit platform as a whole. Indeed, an often-cited report by Pew Research Centre found that 69% of Reddit users identified as male (Barthel et al. 2016). Following the statistically significant increase in female users in the 2018 census, some users expressed surprise about the number of responders identifying as female, as their community experience was male-dominated:
(3)
These comments are particularly notable as
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involved members of the community view it as male-dominated suggests that the continued (although decreasing) bias towards male users in the census may be an accurate depiction of the demographics of the community.
Age Very different age categories were used in the first Popheads census when compared to the latter two, so the findings are presented below in two separate graphs.
30%
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15%
10% Percentage Percentage of users
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0% 0-14 15-16 17-18 19-20 21-22 23-24 25-29 30-39 40-49 50-59 60+ Age range
Figure 4.4: Self-reported age of Popheads users in February 2016. 50% 45% 40% 35% 30% 25% 20%
15% Percentage Percentage of users 10% 5% 0% 0-13 14-17 18-21 22-25 26-29 30-33 34-37 38-41 42-45 46-49 50+ Age range
Apr-17 Apr-18
Figure 4.5: Self-reported age of Popheads users in April 2017 and April 2018. 75
Firstly, it is remarkable how similar the age data is despite spanning a three-year period and the number of responders increasing by 144% from the first census to the last. This suggests that there is a good degree of continuity in this demographic variable. Figures 4.4 and 4.5 show that older teenagers (17-18 onwards) and people in their early 20s are the most likely to be Popheads users. Membership decreases dramatically in the 26- 29 age group and then continues to decline through all of the other age categories. In 2016, there were no users over the age of 39. The 2017 data concluded that only 0.8% of responders were over the age of 38, and only 0.2% were over the age of 46. These numbers increased in 2018 but only marginally: 1.1% of members reported being over 38 and 0.3% over 46. Overall, then, Popheads is a very young community and fairly homogenous in its age distribution. This is perhaps unsurprising when one considers the subject matter of the community. However, this does have interesting sociolinguistic implications as variationist studies have consistently linked language innovation with young people (Eckert 1988; Mendoza-Denton 2008; Tagliamonte 2016).
Sexuality Another interesting finding is that in the 2017 and 2018 censuses over 50% of responders identify as lesbian, gay, bisexual, or pansexual, an increase from 34% in the 2016 census.
heterosexual
non-heterosexual
other/no response
0% 10% 20% 30% 40% 50% 60% 70% Percentage of users
Feb-16 Apr-17 Apr-18
Figure 4.6: Self-reported sexuality of Popheads users.
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Elsewhere, outside of the context of the census, multiple users characterise Popheads as an LGBT+ orientated space. For instance, a user who identifies as a straight male writes that the community has a "sort of gay humour" which he finds funny (
Ethnicity In terms of ethnicity, the results remain relatively consistent across the censuses. Caucasian responders are the most frequent across all of the datasets (although the percentage decreases from 63% to 59% over the lifespan of the community), Asian is the second most frequent ethnicity recorded, followed by Hispanic, and Black/African American.
Caucasian/white
Asian
Hispanic
African-American/Black
Middle Eastern
Other/No response
0% 10% 20% 30% 40% 50% 60% 70% Percentage of users
Feb-16 Apr-17 Apr-18
Figure 4.7: Self-reported ethnicity of Popheads users.
Country of origin The Popheads census also polls users on their country of origin. It is somewhat difficult to succinctly report this data, as the categories changed every year and there was seemingly some confusion among responders about which category represented their country.
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Therefore, the data has been simplified to look only at the percentage of Popheads members who report being from North America (that is, Canada or the USA). As can be seen in Figure 4.8 below, across all three years, North American participants make up the greatest share of Popheads members, representing 73% of responders in 2016, 65% in 2017, and 64% in 2018.
North America
Other
0% 10% 20% 30% 40% 50% 60% 70% 80% Percentage of users
Feb-16 Apr-17 Apr-18
Figure 4.8: Percentage of Popheads users from North America.
English as First Language The vast majority of Popheads members report that English is their first language. Nevertheless, the number of members who have English as their second language has increased over the years from (a not unsubstantial) 14% in 2016 to over 21% in 2018.
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Native English Speaker
Non-Native
no answer
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Feb-16 Apr-17 Apr-18
Figure 4.9: Percentage of Popheads users with English as their first language.
To summarise, Popheads members are more likely to be male than female, they are very likely to be under the age of 40 (with most in their teens or early 20s), they are equally likely to be heterosexual and non-heterosexual, and they are most likely to be Caucasian, from North America, and have English as their first language.
The moderators
Moderation in Popheads is undertaken by volunteers (who are named on the homepage of the community) who dedicate their time and efforts to safeguarding the community, setting and enforcing community rules and expectations, and planning community practices. By the end of the data collection period in May 2018, thirty-six different members had served as moderators of the community. However, there had never been more than sixteen moderators at any one time. On Reddit, the person who creates the community (in this case,
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interested users to apply to be a moderator, adding that he would "pretty much accept everybody that comments in this thread" (
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monodimensional top-down concept, then moderators would appear at the top of the hierarchy of the community.
Language creativity
The Popheads community is a locus of linguistic creativity, and the distinctive and stylised linguistic repertoire of the community is informed and influenced by a wide range of (primarily digital) external sources. For instance, slang derived from online environments plays a large role in the Popheads' lexicon, with forms such as GOAT (an acronym of 'greatest of all time') and thot (an acronym of 'that ho over there'; broadly synonymous in usage with 'slut') occurring frequently in the Popheads corpus:
(4)
In addition to forms used in wider internet slang, slang forms used specifically in online 'Stan culture' are also prevalent in the community. Stan culture refers to online fandom communities (and especially those based on the microblogging platform Twitter). It takes its name from the protagonist of rapper Eminem's 2000 single 'Stan', a song about an obsessed fan. An example of a term taken from Stan culture that is used widely in the Popheads community is skinny legend, which is used to glorify popstars and other noteworthy people (regardless of their weight or body shape):
(6)
Another source of linguistic creativity in the Popheads community is viral internet memes which are adapted and incorporated into the repertoire of the community. Internet
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memes are defined by Shifman (2013: 367) as "units of popular culture that are circulated, imitated, and transformed by individual Internet users, creating a shared cultural experience in the process". For instance, in 2016, a meme began circulating on social media in which pictures of unappetising looking meals were captioned with intentionally ludic phonologically-influenced non-standard spellings of the French culinary salutation bon appétit, including bone apple tea, bone app the teeth. A year later, pop star Katy Perry released a song named bon appétit and Popheads members revived the meme when disparagingly referencing the song:
(8)
Another common source of creative forms used in the Popheads community is LBGT+ culture and especially the drag ballroom culture of the 1980s and 1990s. Examples of terms regularly used in Popheads which are derived from LGBT+ culture include throwing shade (to insult someone), fierce (something exceptionally good), and hunty (a blend of honey and cunt; typically used to irreverently address friends):
(10)
Popheads users are very aware of their creative shared linguistic repertoire and often engage in meta-linguistic discussions about the language used in the community. For instance, in June 2017, Popheads member
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began a thread in which he invited members to discuss their favourite Popheads memes (memes is the term that Popheads members often use to refer to the creative elements of their shared linguistic repertoire) (
Popheads as a Community of Practice
As outlined in Section 2.2, a fundamental tenet of the CofP framework is that communities must meet three specific criteria to qualify as a CofP: 1) members must engage in a joint enterprise, 2) there must be mutual engagement between members of the community, and 3) a shared community-specific repertoire must emerge as a result of the members' engagement in the joint enterprise (Wenger 1998). Below I demonstrate how the Popheads community fulfils each of the three criteria through the discussion of 'rates'. Rates are a defining Popheads practice that see members draw on their specialist shared repertoire as they engage with each other in pursuit of the community's joint enterprise of celebrating, promoting, discussing, and critiquing pop music and members of the pop music industry. Rates involve Popheads members scoring a list of songs, which are typically from the same sub-genre or by ostensibly similar artists. So, for instance, a popular rate in 2016 asked members to rank songs from three commercially successful female pop artists' albums released within the previous three years: Taylor Swift's 1989, Carly Rae Jepsen's E•MO•TION, and Ariana Grande's Dangerous Woman. Rates are highly ritualised. Members submit suggestions for rates to a designated thread. A Popheads member then officially posts the suggestions and members are encouraged to "upvote" or "downvote" to indicate the rates they would like to see and participate in over the coming months. The suggestions with the lowest scores are discarded,
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and the rates with the most upvotes are scheduled to occur over the subsequent four-month period. Each rate has one or more 'hosts', who are members that volunteer to be responsible for all of the administrative duties relating to the rate. Once the rate begins, members who would like to participate submit their rankings of the chosen songs (along with an optional short review) by a specified date to the host(s) via the Reddit Private Messaging system. Users typically have around one month to submit their scores for a rate, and then the results are usually announced one or two weeks later. Popheads utilises a somewhat unusual rating scale: each song must be rated on a scale of 0 to 11. However, each member is only allowed one "11" (designating the best song) and one "0" (designating the worst song) per rate. This system has led to the number 11 taking on special significance in the Popheads community, sometimes to the confusion of newcomers. For instance, in 2018,
1 (13)
In this example, the specialist practices of the community – and the shared linguistic repertoire which is used to articulate them – prove confusing and alienating for newcomers (line 1). An established member,
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(line 9). Rates, then, are not just about ranking songs; they are an intricate and ritualised practice, which draw on the community's linguistic repertoire of specialist jargon and terminology. The scores for the rates are tracked by the rates' hosts, who calculate the average score per song. Then the results are announced in three 'reveal' threads over a three-day period (which typically coincides with the weekend). The three reveal threads take the form of a countdown that occurs throughout the day, with the lowest scoring songs revealed first. The rate reveal threads are very active, with each day's thread often attracting hundreds of comments from Popheads members who are excited to discuss the results of the rate and the music reviewed. Within each thread, there is typically a great deal of extensive mutual engagement and interaction between Popheads members. The joint enterprise of the Popheads community centres on celebrating, promoting, and critiquing pop music and members of the pop music industry. The rates are among the most notable manifestations of the joint enterprise of the community as they involve reviewing and critiquing music, promoting favoured artists, and engaging in extended discussions centred around music. Since part of the joint enterprise of the community is to promote favoured artists, rate threads are typically catalysts for a key aspect of the community's shared repertoire: intense expressions of hyperbolic emotion. Members want to see their favourite artists win the rates, and they express jubilation when their favoured songs or artists perform well and disappointment when they underperform. However, these displays of emotion are typically expressed in an intense, hyperbolic manner for humorous effect. For instance, after a song by Carly Rae Jepsen was announced as the winner of a rate, the user
(14)
Several linguistic techniques are used here by
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Furthermore,
1 (15)
Lines 1-2 interpreted literally, suggest that
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1 (16)
In lines 1-2,
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sentence is not clear; however, considering the context, one could speculate that
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5 Chapter 5: Case study 1 – delete it fat
Introduction
The first case study centres on the expression delete it fat (and its formal variants), which, in the Popheads community, can be glossed as a humorous and playful way of articulating 'I disagree with your opinion' or 'I do not like your comment'. The multiword expression, then, allows Popheads members to discursively construct and express their attitudes towards music, artists, and each other. Typical usages include:
(1)
Chapter 5 first explores the origins of delete it fat and describes how the expression (and its variants) are defined and used in the Popheads community. I then consider the extent to which the innovation and diffusion of delete it fat support the weak-tie theory of language change. Finally, I analyse the relationship between status, hierarchy, power, and the endogenous LCM policy relating to this form.
Community usage
The expression delete it fat emerged from a bizarre viral hoax story concerning the American pop singer Demi Lovato. A Lovato fan, who identified herself by the name Madison, made a Twitter post (via the Twitlonger extension which allows for messages that exceed the maximum number of characters permitted by Twitter) on 11th November 2014. The post (Madison 2014a) alleges that Madison had met Lovato, and the singer had mocked her
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weight, flicked her genitalia, and "spoke whale" to her.4 Madison later claimed that Lovato had messaged her on Snapchat abusing her and she also posted (photoshopped) screenshots of the text below, which she alleged Lovato had Direct Messaged her via Twitter:
I saw that you wrote that twitlonger about how I spoke whale to you why did you expose me fam? Delete it fat Before I fuck you up (Madison 2014b)
Given both the peculiar nature of the story and the photoshopped images Madison provided as 'evidence' of her interactions with Lovato, it would seem that Madison never intended to claim that the events described actually happened. Indeed, celebrity news sites have treated this as an example of a "bizarre, hilarious and obviously fake" viral hoax (Lynch 2014: n.p.). Nevertheless, the anecdote circulated widely in the media and music fandoms (Davies 2015; Gilbride 2015; Rear 2016; Todd 2015; Wass 2015). Following its publication, the story became a meme, with members of various fan cultures adapting the original story to feature different celebrities. Among Popheads members, however, it is delete it fat, taken from the message alleged to be sent by Lovato to Madison, which has become highly salient. In December 2016, a Popheads newcomer posted that they were "excited to check out the subreddit!" (
4 To ‘speak whale’ to someone is to reproduce the noises made by whales as they socialise and communicate with each other. In this context, the reference to whale noises is seemingly meant to be interpreted as an insult about Madison’s weight, with the implication being that she would understand the language of whales as she is the size of a whale. 90
Delete it fat, on the surface level, is a face-threatening imperative utterance (Brown & Levinson 1987: 65), in which the speaker orders the addressee (addressed by the ostensibly pejorative vocative fat) to delete an unspecified referent (it). However, on a pragmatic level, in the Popheads community, delete it fat functions as a playful declarative statement. The speaker's aims are not to advise or order the addressee to delete their comments or opinions, but to express their disagreement or dislike humorously in a way that poses little-to-no threat to the addressee's face needs. Importantly, the use of fat is not intended to be a comment on the addressees assumed body size, and there are no instances in the corpus which indicate that it has been interpreted as an insult. It is merely part of the multiword expression, and it is almost divorced from its original meaning. Indeed, I will demonstrate below that fat can be substituted with a range of other nouns without impacting the meaning of the expression. Above, I argue that, generally, delete it fat is not interpreted literally or understood to be a face-threatening utterance. This is inferred by analysing the interactions between users and observing that it is extremely rare for Popheads members to react negatively to being told to delete it fat. I have only found evidence of one Popheads member being offended when the form was directed at them, and this occurred in a discussion about Ariana Grande:
1 (3)
After
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while
(4)
Here,
(5)
In (5), after
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of telling
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Delete it fat was a valued and important part of the Popheads' community's lexicon from its emergence in August 2016 until well after its ban in January 2017. Indeed, there are multiple instances in the Popheads corpus in which members refer to delete it fat as being highly salient to their shared linguistic repertoire. For instance, in November 2016,
The weak-tie theory of language change
The innovator
If the weak-tie theory of language change's prediction about linguistic innovators holds in the Popheads online CofP, I would expect a peripheral member to be the innovator of delete it fat in the community. Delete it fat was first used in the community in May 2016 in a controversial thread started by a user who asks Popheads members to name their favourite "straight anthems". The person who started this thread deleted their account before their name was archived and they will thus be referred to as
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Popheads member who has since deleted their account and will thus be referred to as
(7)
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term affiliation with the community as he left no later than a month after introducing the expression. This seems to be the status profile of a peripheral member or community outsider. However, there is another factor that needs to be taken into account. After
(8)
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Author
Table 5.1: Status markers for
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Author
Table 5.2: Status markers for
This case study thus provides support for the hypothesis that peripheral members will be the innovators of linguistic forms in an online CofP.
The early adopters
After its successful introduction in August 2016, six early adopters began using the expression. The number of cumulative users more than doubled in September (bringing the total to seventeen), a number which doubled again by the end of October, by which time thirty-seven members had adopted the form. The end of October 2016 serves as the cut off point for the early adoption period: looking at Figure 5.1, it is clear that this point in time marks the start of the s-shaped curve of sociolinguistic diffusion. The early adopters, then, are the 36 people who used delete it fat between its introduction by
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250
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100 Numberusers of
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Jul-16 Jul-17
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May-16 May-17 May-18 Figure 5.1: Cumulative number of users of delete it fat.
This research aims to explore if the weak-tie theory of language change's prediction that early adopters will be central leaders in their network holds in an online CofP. I equate the concept of 'centrality' with scores across multiple status markers which are higher than the community median in the Popheads community. Therefore, to explore the hypothesis, I calculated the percentage of early adopters that scored above, at, or below the community median for each of the eight quantitative status markers of interest in this research (see Figure 5.2 below). I also looked at the percentage of the moderating team who served as early adopters.
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100% 90% 80% 70% 60% 50% 40% 30%
Percentage Percentage of earlyadopters 20% 10% 0% months months submissions comments replies one-link ties ten-link ties median active remaining contributed contributed received formed formed score received
Below the median At the median Above the median
Figure 5.2: Percentage of early adopters of delete it fat who scored above, at, or below the community median for the quantitative status markers.
Months active The findings in Figure 5.2 show that 34.3% of early adopters had been active in the community for longer than the community median time when they adopted delete it fat. This is a relatively small percentage and was somewhat surprising as my ethnographic observations and preliminary examinations of the data suggested that early adopters were, generally, well-established at the time of early adoption. However, further examination showed that the community median for this measure was very high in the early adoption period. In other words, the low percentage of early adopters who scored higher than the community median is not necessarily signifying that the early adopters were relatively new to the community, but rather that full members of the community tended to have been active for many months. Indeed, a breakdown of the number of months that early adopters had been active at the time of adoption (Table 5.3) shows that just 20% of early adopters of delete it fat had been active for three months or less at the time of adoption, while 80% had been active for four or more months, and 22.9% for twelve months or more.
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Months active Percentage of early adopters 1 - 3 months 20% 4 - 11 months 57.1% 12 months + 22.9%
Table 5.3: Number of months that early adopters of delete it fat had been active at the time of uptake.
Overall, then, although 80% of early adopters of delete it fat were established members at the time of update, the majority did not score higher than the community median for this status marker.
Months remaining The findings show that over 71.4% of early adopters remained in the community for longer than the median time, indicating that most were on an inbound trajectory (relative to other members) in the community. Breaking down the number of months that early adopters remain active after the time of uptake (Table 5.4), shows that a remarkable 94.3% of early adopters remain active for at least 12 months after the time of adoption, with just 5.7% leaving within three months of adoption.
Months remaining Percentage of early adopters 0 - 3 months 5.7% 4 - 11 months 0% 12 months + 94.3%
Table 5.4: Number of months that early adopters of delete it fat remained active after the time of uptake.
Submissions contributed Figure 5.2 demonstrates that 85.7% of early adopters contributed more submissions than is typical in the community, indicating a relationship between the practice of contributing content and early adopter status.
Comments contributed A remarkable 88.6% of early adopters contributed more comments than the community median.
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Replies received Figure 5.2, above, shows that 77.1% of early adopters of delete it fat received more replies to their posts than the community median, suggesting that the early adopters were successful at sparking discussion among members.
One-link ties formed The findings show no distinct relationship between 'one-link ties formed' and early adopter status: while 51.4% of early adopters scored higher than expected for this measure, 48.6% scored lower. This almost 50/50 split suggests that this measure is not linked to early adopter status.
Ten-link ties formed In terms of the relationship between 'ten-link ties formed' and early adoption of delete it fat, 60% of early adopters scored equal to the median for this measure (which was a score of 0), indicating that they had not had the sustained mutual interaction with other members which leads to the formation of ten-link ties. Meanwhile, 40% of early adopters scored higher than the median (which, in this case, means that they have formed one or more ten-link ties throughout their time in the community). Therefore, high scores on this measure do not seem to correlate with early adopter status.
Median score received 'Median score received' is another measure which is not strongly correlated with early adopter status: 42.9% of early adopters scored higher than the median, 40% equal to the median, and 17.1% below the median.
Moderators Finally, two of the thirty-five (5.7%) early adopters were moderators. During the early adoption period for delete it fat, there were twelve active moderators in the Popheads community, meaning that 16.7% of the moderating team served as early adopters. As discussed in Section 3.4.6, if there was a general tendency for moderators to be early adopters, I would have expected 55% or more of the team to appear on the list of early adopters.
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To summarise, then, this section explored if early adopters of delete it fat scored higher than the community median across multiple markers of status in order to determine if the weak-tie theory of language change's prediction that early adopters would be high-status members of the community would hold in an online CofP. On the one hand, I found that 71.4% of early adopters scored higher than the community median for 'months remaining', 85.7% for 'submissions contributed', 88.6% for 'comments contributed', and 77.1% for 'replies received'. Collectively, these findings indicate that most early adopters were on an inbound trajectory into the community and were relatively prolific contributors of content which sparked discussion in the community Nevertheless, while the majority of early adopters did score highly across these four measures of status, a minority did not: 28.6% of early adopters scored equal or lower than the community median for 'months remaining', 14.3% for 'submissions contributed', 11.4% for 'comments contributed', and 22.9% for 'replies received'. These reasonably high numbers do not necessarily invalidate the above conclusion. However, they do highlight the importance of being wary of generalisations about the way early adopters may or may not behave in an online CofP. Moreover, while the majority of early adopters tended to score highly on the four status markers discussed above, the other five status markers ('months active', 'one-link ties formed', 'ten-link ties scored', 'median score', and 'moderator status') did not appear to be linked to early adopter status. These findings provide support for the underlying prediction explored in this thesis that the relationship between power and status may be more complicated in CofPs than is typically accounted for in much of the contemporary sociolinguistic work. Specifically, these findings suggest that not all of the status markers are created equal, and some are more associated with specific acts of influence than others. Therefore, in order to interrogate this complex relationship further, I turned to look at RQ1.3, which asks which (if any) of the status markers are statistically significant predictors of early adopter status. In contrast to the relatively simplistic quantitative analysis employed above, here, I employ principal component analysis (PCA) and logistic regression to better understand the potentially complex and multidimensional nature of the relationship between early adoption and status. In this analysis, the status markers for the thirty-five early adopters of delete it fat were studied alongside the status markers of the 1,009 users who were full members of the Popheads community during the early adoption period but who did not take up the expression.
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The first step was to determine if there were any strong correlations (signified by a Spearman value of 0.7 or above) between the status markers in the early adopter/non-adopter dataset. Strong correlations could bias the results as they would essentially be measures of the same phenomenon. However, as illustrated in Figure 5.3, below, there are no strong correlations between any of the status markers in the delete it fat adopter/non-adopter dataset: all correlations have Spearman correlation coefficient scores of 0.58 or lower.
Figure 5.3: Correlation matrix for the early adopter/non-adopter delete it fat dataset.
With that established, the next step was to conduct a principal component analysis (PCA). As discussed previously, this research proceeds on the presupposition that power may be a multidimensional concept that cannot easily be reduced to a single hierarchy. To recap the discussion of PCA in the methodology, PCA transforms the numerous variables associated with status in the inputted datasets into more simplified principal component
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variables (PCs), which retain most of the information in the original dataset and allow for a multidimensional overview of status. The PCA on the delete it fat early adopter/non-adopter dataset identified ten PCs which collectively accounted for the majority of the variance (information) in the dataset. As outlined in the methodology, the two PCs which account for the greatest proportion of variance in the dataset are explored in-depth, as are (if applicable) any other PCs which individually account for more than 5% of the variance. However, as illustrated in Figure 5.4, PC3 – PC10 individually account for less than 5% of the variance of the dataset, and thus it is only PC1 and PC2 which will be explored further in this instance.
100% 93.38% 90%
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10% 4.24% 1.75% 0.34% 0.25% 0.04% 0.00% 0.00% 0.00% 0.00% 0% PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 Figure 5.4: The proportion of variance accounted for by the principal components identified in the early adopter/non-adopter delete it fat dataset.
Figure 5.4 shows that 93.38% of the variance in the dataset can be accounted for by PC1 alone, indicating that this variable is crucial to further analysis. In PCA, 'loadings' describe the extent to which each of the original variables in the inputted dataset (in this case, the status markers) contributed to the PCs. A very high loading number (either positive or negative) indicates that the original variable has a strong relationship to the PC (that is, the original variable was a crucial factor in the creation of the component).
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Comments contributed 1.00
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Figure 5.5: Loadings for PC1 in the early adopter/non-adopter delete it fat dataset.
Figure 5.5, above, shows the loadings for PC1 and demonstrates that 'comments contributed' is, by far, the most notable contributing factor to this PC, and the other variables had little input. Therefore, PC1 will be known as 'commenting behaviour'. Meanwhile, PC2 accounts for 4.24% of the variance in the dataset (Figure 5.4). This variable is composed primarily from the original status marker 'months remaining', with 'months active' also being a very small contributing factor (Figure 5.6). PC2 will thus be referred to as 'inbound/outbound trajectory'.
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Months remaining 1.00
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Figure 5.6: Loadings for PC2 in the early adopter/non-adopter delete it fat dataset.
Now, 97.36% of the variance in the delete it fat early adopter vs non-adopter dataset can be explained by just two variables: PC1 (commenting behaviour), and PC2 (inbound/outbound trajectory). Figure 5.7 below shows the scores for each of the early adopters and non-adopters of delete it fat across these two variables. Figure 5.8 is a simplified version of the same graph with the extreme values removed to enable better visualisation of the key patterns.
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Figure 5.7: Plot showing scores on PC1 and PC2 for members included in the early adopter/non- adopter delete it fat dataset.
Figure 5.8: Simplified plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter delete it fat dataset.
In terms of PC1 (commenting behaviour), 81% of non-adopters score very low on this marker and cluster between the -16 and 0 points on the x-axis, suggesting that they are
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relatively infrequent Popheads commenters. In contrast, 69% of early adopters score positively on this dimension, suggesting a greater level of commenting prolificness among this group. This discovery is unsurprising given the finding above that 88.6% of early adopters contribute more comments than the community median. When PC2 (inbound/outbound trajectory) is considered, non-adopters appear all along the y-axis, indicating diverse trajectories among this group: 64% score positively (indicating that, relative to other members, they are on inbound trajectories) and 36% score negatively (suggesting they are on outbound trajectories). In terms of the early adopters, 89% are clustered on the positive side of the y-axis, indicating that most members of this group are on inbound trajectories. Moreover, it would appear that there is an interaction between PC1 and PC2 when it comes to early adoption. A large percentage of both non-adopters and early adopters regularly score positively for PC2 (64% and 89% respectively). However, of the 647 non- adopters who score positively for PC2, only 129 (19.9%) also score positively for PC1. In contrast, of the 31 early adopters who score positively for PC2, 22 (71%) score positively for PC1. In other words, it would seem that scoring high on both PC2 (that is, remaining in the community for an extended period after the point of early adoption) and PC1 (indicating relatively prolific commenting behaviour), may also be a predictor of early adopter status. Next, a logistic regression was performed to determine if PC1 and PC2 can be considered statistically significant predictors of early adopter status in the delete it fat case study. Early adopter status served as the response/dependent variable, and the two predictor/independent variables were the scores for each of the early and non-adopters on PC1 and PC2 respectively. Based on the findings above regarding a possible relationship between PC1 and PC2, an interaction between the two variables was also considered.
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Input (early adopter) 0.034 Total N 1044
Deviance residuals: Min 1Q Median 3Q Max -1.268 -0.2032 -0.1812 -0.1475 3.3687
Coefficients: estimate standard z value p value error (Intercept) -4.05889 0.264934 -15.32 p < 0.0001 PC1 (commenting 0.01515 0.003761 4.029 p < 0.0001 behaviour) PC2 0.133217 0.047261 2.819 p < 0.01 (inbound/outbound trajectory) PC1:PC2 (interaction) 0.007139 0.001807 3.95 p < 0.0001
Degrees of freedom: 1043 total; 1040 residual Null deviance: 306.5 Residual deviance: 237.8 Akaike’s information 245.8 criteria (AIC) Table 5.5: Logistic regression model for the factors predicting early adopter status in the early adopter/non-adopter delete it fat dataset.
The results show that PC1, PC2, and an interaction between the two are statistically significant predictors of early adopter status. Nevertheless, a Tjur's R2 test (which assesses the predictability of the logistic regression model) shows that the model is a relatively weak fit, with an R2 score of 0.16 (a score of 0 means the model is unsuccessful, a score of 1 means that the model is a perfect fit). In other words, although the predictors have a significant relationship with adopter status, this finding suggests that there are also other factors at play which affect early adopter status that this study does not take into account.
Conclusion
To summarise, this section was concerned with the applicability of the weak-tie theory of language change to online CofPs. Firstly, I concluded that
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community. Thus, there was evidence to support the idea that innovators would be peripheral members of the community. Secondly, I found that there was some evidence to support the hypothesis that the early adopters in a CofP would be high-status members. Specifically, I showed that 71.4% of early adopters scored higher than the community median for 'months remaining', 85.7% for 'submissions contributed', 88.6% for 'comments contributed', and 77.1% for 'replies received'. However, other status markers (such as 'one-link ties formed', 'ten-link ties formed', 'month active', 'median score received', and 'moderator status') did not seem to have a strong relationship with early adopter status. These findings suggest that the underlying assumption in this research that the relationship between power and status may be more complicated than acknowledged in much of the CofP literature could be correct. Consequently, I turned to look at RQ1.3, which interrogates which (if any) of the status markers are statistically significant predictors of early adopter status. I concluded that PC1 (commenting behaviour) and PC2 (inbound/outbound trajectory) are both statistically significant predictors of early adopter status. Additionally, there is a statistically significant interaction between PC1 and PC2, meaning that being a relatively prolific commenter and also remaining in the community for a long time is a multidimensional interactional predictor of early adopter status.
Status, hierarchy, power, and the delete it fat LCM policy
In this section, I analyse the relationship between status, hierarchy, and power in the Popheads CofP through an exploration of the endogenous LCM policy relating to delete it fat. Specifically, I focus on issues of status, hierarchy, and power relating to the advocation for the LCM policy, its implementation, and its effectiveness.
Advocation for the LCM policy
The events which led to the banning of delete it fat began on 20th November 2016 when the moderators banned 'shitposts' from the community. Shitposts are intentionally surreal, bizarre, or inane posts which are primarily designed to be humorous and are sometimes perceived by other members as low-quality content. An example of a shitpost identified by 111
the moderator who announced the ban was a remix of an Ariana Grande song in which a lyric about a "dick bicycle" had been inserted after every line. The reaction to the banning of shitposts was mixed: most users who commented on the announcement thread welcomed the changes, but some complained about censorship. Nevertheless, one of the moderators avowed that "just bc [because] a portion of the sub doesn't like the change doesn't mean that we're not going through with cracking down on shitposts" (
1 (9)
For these two members, delete it fat is one of the factors linked to a perceived decline in quality in the community. Although
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Less than two weeks after the initial comments from
1 (10)
Notably, it would seem that the detractors of delete it fat, in this discussion at least, do not object to the phrase itself but rather resent its perceived ubiquity. Both
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became overused in the community.
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Figure 5.9: Raw and normalised frequency of delete it fat in the Popheads corpus.
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understands, however, that other members do not feel the same and advises
in the community. It is reasonable to conclude that these four members' often strongly- worded complaints were influential in the decision to introduce an LCM policy which banned the use of the form in the Popheads community. In Table 5.6, below, I compare the status markers for these users at the time of their complaints to the community medians for the status markers at that time. Remarkably, all four of the members whose complaints about delete it fat seemed to be influential in its banning score higher than the community median on at least four status markers. All four members contributed at least ten times more comments than the community median, meaning that they were highly prolific. Moreover, all four remained in the community for longer than the community median time (and were still active at the end of the data collection period), suggesting they were on inbound trajectories in the community. Three of the four had also posted more submissions, received more replies, and formed more ten- link ties than expected. Other status markers, however, do not necessarily seem to be related to influencing the creation of LCM polices. For instance, only two of these users had been active in the community for longer than the community median time (with one, in fact, even being a newcomer to the community), only one had a high score for 'one-link ties formed', and none of these users scored higher than expected for 'median score received'. There are too few users on record complaining about delete it fat to undertake further statistical analysis (such as a logistic regression) to make more definitive conclusions. However, from this impressionistic analysis, it is possible to conclude that the members who seemed to have been influential in the introduction of LCM score highly across multiple unofficial hierarchies of status in the community: they are not just 'typical' members of the CofP.
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Author
Table 5.6: The status markers of Popheads members who may have been influential in the introduction of the delete it fat LCM policy.
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Implementation of the LCM policy
On 1st January 2017, the moderators officially announced that delete it fat was among several comments which were now forbidden in the community and that instances of the comments would be removed by the moderators and result in warnings or bans for repeat violators. There is no evidence in the corpus that any members were ever banned for violating the LCM policy; however, there is evidence, as will be discussed shortly, that the moderators removed some comments containing the expression. An edited version of the delete it fat LCM announcement is reproduced below:
1 (11) Happy New Year!!! 2 In 2017, we want to establish a new standard for quality and friendly discussion 3 on r/popheads. 4 New Rules Regarding Commenting 5 Lately, we've been seeing a lot of low-effort, biased (and often mean-spirited) 6 comments that kill actual discussion. These make the subreddit seem less like a place 7 to truly discuss pop music, and less welcoming, and more like replies on Stan 8 Twitter™️ or an ATRL post. 9 Therefore, in 2017 we will actively be removing these low-effort comments and be 10 taking action towards the people that habitually post them. We promise that the 11 overall quality of discussion will go up. And honestly, if you don't like that we're 12 removing comments or you feel like your comments will be affected... we encourage 13 you to leave and try ATRL instead. 14 Examples of comments that will be removed/prompt warnings for repeated usage:
15 • emojipastas 16 • "keep it" 17 • "delete it fat" 18 • "buy x on itunes" 19 • "artist x is over" 20 • attacking certain artists in every comment you make 21 • stanning for certain artists when it's not relevant 22 • "artist x did it better"
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23 • memes that are beating a dead horse 24 • excessive shitposting 25 Thanks in advance for your cooperation. Please make this r/popheads' New Year's 26 resolution <3 (
This announcement was posted by
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The moderators write in their announcement, "if you don't like that we're removing comments or you feel like your comments will be affected [...] we encourage you to leave and try ATRL instead" (lines 11-13). In this strongly-worded post, members are told that they must submit to the moderators using their top-down powers to exercise their authority and remove other members' content or else they are no longer welcome in the community and should join the infamous outgroup instead. Here then the moderators essentially redefine who can be a Popheads member and what being a member of the community means. I hypothesised that the moderators arguably heavy-handed approach to the banning of delete it fat, and, specifically, how LCM is implemented to gatekeep and discursively redefine membership, might cause significant controversy in the community. However, although several members were unhappy about the content moderation (as I will demonstrate below), only one criticised the moderators' tone and explicit top-down display of authority and power in this announcement. Moreover, in a retrospective discussion about the banning of delete it fat, which took place seven months after the events documented above,
(12)
In (12),
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1 (13)
Both of these users explicitly stated that they were pleased about the introduction of content moderation (lines 1 and 5).
1 (15)
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thus being owed appreciation. This kind of discourse is regularly seen in online fandom communities (Stanfill 2013: 126), where fans feel that their idols are indebted to them and owe them something (be it new content, social interactions, and so on) because of the support that they have given them. Arguably the more conventional way of framing the relationship is that members subscribe to the CofP because they have an interest in the joint enterprise of the community. The moderators do an important job in shaping community practices. However, their work is essentially hours of unpaid labour on behalf of the community, with the only 'reward' being the status of being a moderator on a popular subreddit (Seering et al. 2019).
(16)
Here,
(17)
While it is true that it was the moderators who introduced the LCM policy, I have shown that this decision may have been influenced by a small number of non-moderating members of the community who voiced negative views about the expression. However, in the comments
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above, all responsibility for the LCM policy is placed upon the moderators. The role that non- moderators played in the banning of delete it fat through their complaints about the ubiquity of the expression has been figuratively erased from the community's discursive history. In (16),
Effectiveness of the LCM policy
Figure 5.10 shows the raw and normalised frequencies of delete it fat in the Popheads corpus from its first usage until the end of the data collection period in May 2018.
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Figure 5.10: Raw and normalised frequency of delete it fat in the Popheads corpus.
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The LCM policy was highly effective at causing an immediate marked decrease in the frequency of the form. Delete it fat decreased from being used 92 times per million words (PMW) in the corpus in December 2016, to 49 times PMW in January 2017, and 19.33 times PMW in February 2017. Moreover, as well as being effective in the short-term, the LCM policy was also successful in the long-term: the frequency of the form remained relatively low in the Popheads community until the end of the data collection period. One member who was seemingly influential in the introduction of the LCM policy,
(19)
In the complaints about delete it fat which preceded the introduction of LCM, the negative attitudes primarily centred on its over usage in the community. In other words, the problem that some members had with delete it fat was seemingly never related to its form or semantics but to its perceived ubiquity. Although the ban did not erase the phrase from the community, it did reduce it, which essentially solved the issue that most members cited as their primary grievance. Therefore, in this way, the ban can be considered a successful exercise of the moderators' power. However, it is not clear exactly how the moderators' power was successful in decreasing the frequency of delete it fat. Specifically, it is not clear if the frequency decreases were the result of members changing their posting habits to abide by the new LCM policy, the moderators directly intervening and deleting comments which contained the expression, or, perhaps most likely, a combination of both of these factors. Indeed, there is no way to determine how many posts were removed by the moderators for containing the delete it fat form (although, as will be discussed below, there is direct evidence that this did occur). As all the data was collected retrospectively approximately thirty days after posts were created, the text of any comments removed in that period is usually unrecoverable. Nevertheless, the corpus does contain a trace of these removed comments, and it is possible to total the number of posts removed by the moderators each month:
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Figure 5.11: Number of posts removed by the Popheads moderators.
In November 2016 (when shitposts became subject to LCM) the number of removed posts increased. This was followed by another dramatic increase in removed posts in January 2017 (seeing a remarkable 560 posts removed) when the delete it fat LCM policy was introduced (alongside several other LCM policies). However, there is no way to know for sure what percentage of these posts were removed by the moderators for violating LCM policies, as opposed to violating other miscellaneous community rules such as the posting of spam. Therefore, Figure 5.11 can only be interpreted speculatively. However, regardless of whether the frequency decreased because members changed their linguistic behaviour or moderators actively deleted comments, it was the moderators' top-down exercise of their power that led to the decline in the frequency of the banned form. However, while the frequency of delete it fat did decrease, the banned expression was not eliminated from the community, and it continued to diffuse through the CofP. As well as using the standard form, members began to use variant spellings and what I refer to as 'synonym variants' to violate and subvert the LCM policy. For instance, the following comments were retrieved from the thread announcing the delete it fat ban:
(20)
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The variant used by
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Figure 5.12: Monthly usage of synonym variants of delete it fat vs all other forms of the expression.
Moreover, on the same day as the ban, the following comment chain appeared in the corpus:
(21)
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The first comment from
(22)
Although
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expression as undermining the new rules and the authority of the moderators. Moreover,
(23)
Here
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Figure 5.13: Image uploaded to Popheads by
Here then, subverting the content moderation policy rule is turned into a game. Several different users reply to
(24)
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the post itself. Meanwhile,
(25)
These subversive types of constructions allow members to use the banned expression and convey the intending meaning to the addressee(s), while simultaneously passing metalinguistic commentary and framing the banned form as something which they have
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either chosen not to articulate or have been prevented from articulating by the community rules. There is some evidence that the variations of delete it fat are interpreted as subversive by at least one of the moderators. A few days after the ban, on 3rd January 2017, in response to a comment from
(28)
On the one hand, in this statement,
(29)
When we take into account his message to "pls stop", the removal of the comment which sparked the discussion, and his previous complaints about delete it fat variants, it would seem that
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A strong case could be made that users who violate the LCM policy have a certain type of power of their own in that they, for whatever reason, decide to subvert the top-down rules introduced and enforced by the moderators of the community. The power comes from the fact that they are taking back control of parts of the community's linguistic repertoire that have been closed off to them. In total, there were 269 violations of the delete it fat LCM policy by 159 members of the community. Figure 5.14 shows that every single one of these members had at least one status marker higher than the community median, 83% had at least three and 45.2% at least five.
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Figure 5.14: The number of status markers on which the violators of the delete it fat LCM policy score higher than the community median.
Meanwhile, Figure 5.15 provides an overview of the most frequently observed high status markers among the LCM violators. 'Comments contributed' was the status marker that the vast majority (92%) of LCM violators scored highly on, followed by 'submissions contributed' (75%), and 'replies received' (58%). In contrast, 'median score received' (52.8%), 'ten-link ties formed' (43.4%), 'one-link ties formed' (42.8%), 'months active' (32.1%), and 'months remaining' (29.6%) do not appear to be markers linked to the violation of the delete it fat LCM policy.
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0% Comments Submissions Replies Median Ten-link ties One-link ties Months Months contributed contributed received score formed formed active remaining received Figure 5.15: The status markers on which violators of the delete it fat LCM policy score higher than the community median.
In other words, then, the members who take back control of the banned linguistic forms tend to score highly on multiple markers of status. They tend to be prolific contributors in the community (in terms of both comments and submissions), and their posts tend to generate more discussion than is typical. Notably, however, I am not claiming that individuals who score highly for these status markers are more likely to be violators (further statistical analysis would be needed to make that claim), but rather that of the violators, these are the status markers that they tend to score highly on. The final status marker not considered here yet is 'moderator status'. As the LCM policy was introduced and enforced by the moderators, I did not expect any moderators to have violated the policy themselves. As a matter of fact, however, 7 of the 159 delete it fat LCM violators were moderators of the community at the time that they used the banned form (representing 24.1% of the 29 members of the moderating team). These seven moderators used delete it fat (and its variants) a combined total of fourteen times in the seventeen months following the ban (meaning that moderators accounted for 5.2% of all delete it fat LCM violations). Perhaps the most remarkable moderator violation occurred in July 2017.
(30)
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What is so remarkable about this use of the banned expression is that
Figure 5.16: Screenshot of a gif uploaded to Popheads by
Similarly, a month after the above,
(31)
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moderators to find and report delete it fat comments).
(32)
disappointed (23/08/2017 01:45, 19)
Although the moderators did not ban
Conclusion
To conclude this section on status, hierarchy, power, and the delete it fat LCM policy, I have shown that a small number of members complained about the perceived ubiquity of the phrase in the community in the two months leading up to the ban. These members were not moderators, but they did score highly on other status hierarchies – such as 'comments contributed' and 'months remaining' –and thus these status markers seem to correlate with the ability to influence the introduction of LCM policies in the community Prior to the ban, three LCM strategies were proposed. The first involved individual members self-moderating their language to improve the community for the collective. The second was a democratic approach which gave members the power to post what they wanted
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on the understanding that other members would downvote content that they did not like. Finally, the third strategy was a top-down approach, in which undesirable comments were reported to moderators, who would then delete the ones which met some unspecified criteria. On the 1st January, the top-down delete it fat LCM policy was introduced in the community. Members were told by the moderators that comments containing the form would be deleted from the community and that repeat offenders may be banned. This was a top- down policy as it was only moderators who had the power and ability to enforce the stated punishments (that is, comment removal and the banning of users) in the community. Moreover, the moderators simultaneously linked delete it fat to the lexicons of noted outgroups and discursively redefined membership in the community to exclude users who wished to continue using the expression. Despite more individualistic or democratic alternatives having been proposed, an explicit top-down approach to controlling the linguistic repertoire of the community was put in place by the moderators and announced in a way that was characterised by some non-moderating members as "heavy-handed" and "harsh". After the ban was in place, it was violated multiple times by some of the moderators of the community, with one of the moderators even boasting that his privileged position in the moderator hierarchy permitted him to use the banned expression. In contrast, both he and his fellow moderators removed comments and chastised other non-moderating members for violating the LCM policy. Although the moderators' use of their top-down power was effective, both in the short and long term, at dramatically reducing the frequency of the form in the community, some non-moderating members defied the ban and continued to use delete it fat. I showed that members gleefully took pleasure in using variants of the banned expression to subvert the new rules and, in some cases at least, to undermine the power of the moderators. This was a particularly relevant phenomenon in the immediate aftermath of the ban as a direct rebellion to its introduction. All members who defied the ban had at least one status marker higher than the community median, 83% had at least 3, and 45% at least 5. This suggests a relationship between the power to take back control of the community's lexicon and high status on hierarchies unrelated to moderation.
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6 Chapter 6: Case study 2 – buy x on iTunes
Introduction
The second case study focuses on the expression buy x on iTunes (and its formal variants), where x is typically the name of a pop song or album which is significant to individual members, the community as a whole, or the context of the conversation in which it is used. Typical concordance lines featuring this expression include the following:
(1)
This chapter first analyses how the form is used in the Popheads community, before exploring how the discursive patterns associated with the expression are ludically disrupted in instances of linguistic creativity by Popheads members. I will then consider the extent to which the innovation and diffusion of this form support the weak-tie theory of language change. Finally, I explore the relationship between the buy x on iTunes LCM policy, status, hierarchy, and power in the Popheads community.
Community usage
On the surface level buy x on iTunes is an imperative utterance, in which the addressee is ordered to purchase x (which is almost always the name of a song or album) via the popular digital media store iTunes. In the literal interpretation of the expression, the lack of politeness markers or attempts to minimise the imposition of the imperative could be read as a bald on- record strategy (Brown & Levinson 1987: 69), making the form a highly discourteous utterance to direct at one's fellow community members. However, as with delete it fat, the
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literal (impolite) interpretation is not the one which pertains to usage in the Popheads community. When Popheads members tell each other and outsiders to buy x on iTunes, they are not issuing an imperative command which they believe will be acted upon, and the addressees generally understand that no imposition is placed upon them. Consider the following exchange:
(4)
(5)
The first comment was posted in a thread about Lady Gaga single 'The Cure' and, although
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using the expression to linguistically perform and avow his new fandom to her via the promotion of her album CollXtion II. As with delete it fat, there was meta-linguistic evidence that buy x on iTunes was highly salient to community members. For instance, in October 2016 buy emotion on iTunes was named by
(7)
This comment received a score of 28 and a reply from another user suggesting more songs to "buy on iTunes". Furthermore, in a thread celebrating the first anniversary of the Popheads community, three of the comments were variations of the buy x on iTunes form:
(8) <7hothe>: Buy Glory on iTunes! (22/08/2016 16:18, 14) (9)
The repeated use of the expression in posts related to the identity of the community suggests that it serves an affiliative purpose (Zappavigna 2011; Zappavigna 2012) and as a positive identity practice (Bucholtz 1999), helping Popheads users construct their identities as
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members of the CofP. Buy x on iTunes likely serves an affiliative purpose because of how closely this expression is bound with the joint enterprise and shared practices of the community. As discussed above, the expression allows users to explicitly perform their individual (and collective) identities as pop music fans and fans of specific artists and songs. Consequently, the expression has almost become a mutable slogan that users employ to signal engagement with the community's key practices. However, while buy x on iTunes can be used to express community affiliation, it can also be used to dismiss antagonistic users. This phenomenon is best exemplified in a 2016 exchange between a fan of metal music and a Popheads member:
(11)
After reclaiming the homophobic slur used by
(12)
Furthermore, the expression can appear in an 'elaborated form', when the writer adds additional commentary to the standard form. These elaborations can take the form of
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politeness markers such as variants of please or thanks (13 and 14), justifications or incentives to buy x (14 and 15), listing multiple x's to buy (16) or listing multiple methods (in addition to iTunes) to acquire x (17):
(13)
Tinashe], needs all the help we can give (05/02/2017 19:19, 6) (15)
Aside from the variations documented above, and, of course, the open noun phrase slot represented by x, the form of the expression is not a locus for creativity. Instead, creativity tends to arise from ludic subversions of the discursive patterns associated with the expression. For instance, in many cases, the name of the artist who performs x is typically not given in the form and is not determinable from the surrounding linguistic context. Outside of the context of the community, it is likely that these variants would violate Grice's maxim of quantity (Grice 1975) and be an ineffective way of performing fan identities. However, because of the relatively insular nature of the CofP, regular members are typically able to use their shared pop culture knowledge to determine the contextual information needed to interpret the expression correctly. However, one form of creativity surrounding buy x on iTunes sees members ludically play with the consequences of the violation of the maxim of quantity. Consider the following interaction:
1 (18)
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1 (19)
1 (20)
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3
Although conversations such as the ones exemplified in (19) and (20) above ostensibly indicate that an addressee has interpreted the command literally and is refusing to 'obey', it is more accurate to interpret these exchanges within a play frame. For instance,
The weak-tie theory of language change
The innovator
Buy x on iTunes was first used in March 2016, five months into the community's lifespan, in a thread entitled "Why did Taylor pretend like she wasn't okay with the Kanye line?" (<[deleted]> 10/03/2016 05:50, 0). This question relates to a celebrity scandal that occurred in
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2016 involving Taylor Swift, Kanye West, and Kim Kardashian. Taylor Swift's claim that she had not given permission for Kanye West to use her name pejoratively in a song was ostensibly exposed as a lie after Kim Kardashian leaked a video of Swift seemingly giving her blessing for him to release the song. It would seem that the thread was inviting members to gossip or post mean-spirited speculations about Taylor Swift's motivations and character (the post which started the thread was removed and only the title remains, so this cannot be confirmed definitively). The post only received one reply before it was removed by moderators and that was from
(21)
'New Romantics' is a song by Taylor Swift. Therefore,
Table 6.1: Status markers for
Although
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Nevertheless,
The early adopters
After its introduction to the CofP in March 2016, buy x on iTunes had a slow but steady diffusion process over the subsequent months (see Figure 6.1). However, diffusion picked up relatively rapidly in December 2016, and thus the end of November 2016 serves as the cut off point for the early adoption period. The early adopters of buy x on iTunes, then, are the 60 people who used the expression between its introduction by
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300
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Numberusers of 100
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0
Jul-16 Jul-17
Jan-17 Jan-18
Jun-16 Jun-17
Oct-16 Oct-17
Apr-16 Apr-17 Apr-18
Sep-17 Sep-16 Feb-17 Feb-18
Dec-16 Dec-17
Aug-16 Aug-17
Nov-17 Nov-16
Mar-16 Mar-17 Mar-18
May-16 May-17 May-18 Figure 6.1: Cumulative number of users of buy x on iTunes.
In order to explore if the weak-tie theory of language change's prediction that early adopters would be high-status members of the online CofP holds, I first looked at the percentage of early adopters that fell above, at, or below the community median for each of the eight quantitative status markers of interest in this research (see Figure 6.2 below). I also calculated the percentage of early adopters that were active moderators.
100% 90% 80% 70% 60% 50% 40% 30%
20% Percentage Percentage of earlyadopters 10% 0% months months submissions comments replies one-link ties ten-link ties median active remaining contributed contributed received formed formed score received
Below the median At the median Above the median
Figure 6.2: Percentage of early adopters of buy x on iTunes who scored above, at, or below the community median for the quantitative status markers.
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Months active As in the delete it fat case study, only a relatively small percentage of early adopters (33.3%) had been active for longer than the community median. However, again, the community median for 'months active' was high throughout the early adoption period (varying between 7 and 8 months). Indeed, the breakdown of the data for early adopters of buy x on iTunes in Table 6.2 shows only 20% of early adopters were newcomers at the time of uptake, with 80% having been active for four months or more.
Months active Percentage of early adopters 1 - 3 months 20% 4 - 11 months 61.7% 12 months + 18.3%
Table 6.2: Number of months that early adopters of buy x on iTunes had been active at the time of uptake.
Months remaining Figure 6.2 shows that 65% of early adopters of buy x on iTunes remained in the community after the point of adoption for longer than the community median time. This number is slightly lower than the 71.4% who remained for longer in the delete it fat case study. However, it nevertheless suggests that the majority of early adopters were on an inbound trajectory. Indeed, Table 6.3 below, illustrates that just 6.7% of early adopters leave the community within the first three months of early adoption, with 93.3% remaining in the community for at least another four months, and 81.7% for over a year.
Months remaining Percentage of early adopters 0 - 3 months 6.7% 4 - 11 months 11.7% 12 months + 81.6%
Table 6.3: Number of months that early adopters of buy x on iTunes remained active after the time of uptake.
Submissions contributed
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Figure 6.2 shows that 86.7% of early adopters contributed more submissions than the community median. This finding is consistent with the delete it fat case study, where 85.7% of early adopters were relatively prolific submission contributors.
Comments contributed A remarkable 96.7% of early adopters of buy x on iTunes contributed more comments to the community than was typical for a Popheads member (only two early adopters did not break the community median threshold). Again, this is line with the expectations from the delete it fat case study, where 88.6% of early adopters were prolific commenters.
Replies received The findings show that 66.7% of early adopters received more replies than was typical in the community, suggesting that they, by and large, were successful at creating engaging content which sparks discussion. This number, while still notable, is over 10% lower than that seen in the delete it fat case study.
One-link ties formed The results in the delete it fat case study showed that no generalisations could be made about early adopters based on the number of one-link ties they had formed with other members, and this finding is replicated in this case study. Indeed, while 48.3% of early adopters formed more one-link ties than was typical, a comparable 51.7% had formed less than the community median.
Ten-link ties formed Similarly, as with delete it fat, high scores on the 'ten-link ties formed' variable do not correlate with early adopter status. Figure 6.2 demonstrates that 48.3% of early adopters scored equal to the community median for this measure, having formed no ten-link ties, while 51.7% scored above the median, having formed one or more 10-link ties during their time in the Popheads community.
Median score received In another finding congruent with the delete it fat case study, there is seemingly no correlation between 'median score received' and early adoption: 51.7% of early adopters scored higher, 28.3% equal to, and 20% lower than the community median for this measure. 148
Moderators Finally, two of the sixty early adopters (3.3%) were moderators at the time of uptake. There were nineteen moderators active in the community during the early adoption period for buy x on iTunes, meaning that just 10.5% of the moderating team served as early adopters.
In summary, the conclusions reached in the delete it fat case study hold, also, here. When looking at the early adopters of buy x on iTunes, the findings again showed that there were four status markers that the majority of early adopters scored highly on ('months remaining', 'comments contributed', 'submissions contributed', and 'replies received'). Furthermore, the same five status markers ('months active', 'one-link ties formed', 'ten-link ties formed', 'median score received', and 'moderator status') seem, again, to have no correlation with early adopter status. Overall, then, there is evidence here to suggest that early adopters are high-status members of the Popheads community, as predicted by the weak-tie theory of language change. However, that blanket statement and the relatively simplistic quantitative work here do not fully capture the nuance of the interaction between power and early adoption. Thus, PCA and a logistic regression were employed to identify the status markers that were statistically significant predictors of early adopter status In this analysis, the status markers for the sixty early adopters of buy x on iTunes were compared to the status markers for their 1,193 non-adopting counterparts. As a preliminary, a Spearman correlation analysis was performed to determine if there were strong relationships between any of the status markers (Figure 6.3). The highest correlation identified had a Spearman correlation coefficient of 0.57 (a number lower than the 0.7+ which would have indicated a strong relationship), and thus the analysis proceeded unhindered.
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Figure 6.3: Correlation matrix for the early adopter/non-adopter buy x on iTunes dataset.
The subsequent PCA analysis identified ten principal components (PCs) which collectively account for the variance in the dataset. This research analyses the two PCs which account for the highest percentage of the variance plus, if relevant, any additional PCs which account for more than 5% of the variance. However, as indicated in Figure 6.4, only the first two PCs individually account for more than 5% in this instance.
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100% 92.06% 90%
80%
70%
60%
50%
40%
Proportion of variance 30%
20%
10% 5.26% 2.00% 0.37% 0.28% 0.04% 0.00% 0.00% 0.00% 0.00% 0% PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 Figure 6.4: The proportion of variance accounted for by the principal components identified in the early adopter/non-adopter buy x on iTunes dataset.
PC1 accounts for 92.06% of the variance in the dataset (Figure 6.4), and it is thus a crucial variable which will be key to further analysis. Figure 6.5 shows the loadings for PC1: as with the delete it fat dataset, it is clear to see that 'comments contributed' is, by far, the largest contributing factor to PC1 and is more or less synonymous with the original measure. PC1 will thus, again, be referred to as 'commenting behaviour'.
Comments contributed 1.00
Months remaining 0.04
Submissions contributed 0.03
Early adopter status 0.00
Moderator status 0.00
Replies received 0.00
Ten-link ties formed 0.00
One-link ties formed 0.00
Median score received 0.00
Months active -0.01
-0.20 0.00 0.20 0.40 0.60 0.80 1.00 Loadings score
Figure 6.5: Loadings for PC1 in the early adopter/non-adopter buy x on iTunes dataset.
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Meanwhile, PC2 accounted for 5.26% of the variance in this dataset (Figure 6.4). The loadings for PC2, illustrated in Figure 6.6, indicate that 'months remaining' is the largest contributing factor to this PC, with 'months active' playing a very small role. This variable will again be referred to as 'inbound/outbound trajectory'.
Months remaining 0.99
Months active 0.14
Median score received 0.02
Early adopter status 0.00
Replies received 0.00
Moderator status 0.00
Ten-link ties formed 0.00
One-link ties formed 0.00
Submissions contributed -0.01
Comments contributed -0.04
-0.20 0.00 0.20 0.40 0.60 0.80 1.00 Loadings score
Figure 6.6: Loadings for PC2 in the early adopter/non-adopter buy x on iTunes dataset.
Figure 6.7 below shows the scores for each of the early adopters and non-adopters of buy x on iTunes across PC1 and PC2. Figure 6.8 is a simplified version of the same graph with the extreme values removed to enable better visualisation of the key patterns.
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Figure 6.7: Plot showing scores on PC1 and PC2 for members included in the early adopter/non- adopter buy x on iTunes dataset.
Figure 6.8: Simplified plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter buy x on iTunes dataset.
In terms of PC1 (commenting behaviour), 81.9% of non-adopters score very low on this marker and cluster between the -10 and 0 points on the x-axis, suggesting that they are relatively infrequent Popheads commenters. In contrast, 80% of early adopters score
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positively, suggesting a greater level of commenting prolificness among this group. This finding is in line with the numbers above, which showed that 96.7% of early adopters posted more comments than the community median. In terms of PC2 (inbound/outbound trajectory), 61.4% of non-adopters score positively on this variable (indicating they were on inbound trajectories relative to other members) and 38.6% score negatively (indicating they were on outbound trajectories). In terms of the early adopters, 78.3% are clustered on the positive side of the y-axis, indicating that this group are consistently more likely to be on inbound trajectories in the Popheads community. This finding is not surprising given both the similar results in the delete it fat case study and also the fact that 65% of early adopters of buy x on iTunes remained in the community after the point of adoption for longer than the community median time. Moreover, it would appear that there is an interaction between PC1 and PC2 comparable to that observed in the delete it fat case study. Specifically, a large percentage of both non-adopters and early adopters regularly score positively for PC2 (61.4% and 78.3%, respectively). However, of the 732 non-adopters who score positively for PC2, only 143 (19.5%) also score positively for PC1. In contrast, of the 47 early adopters who score positively for PC2, 37 (78.7%) score positively for PC1. In other words, it would seem that high scores on both PC1 and PC2 may serve as a predictor of early adopter status. Next, a logistic regression analysis was performed. Early adopter status served as the response variable, and the scores on PC1 and PC2 were the predictor variables. The significance of the interaction between PC1 and PC2 was also considered.
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Input (early adopter) 0.048 Total N 1253
Deviance residuals: Min 1Q Median 3Q Max -2.0004 -0.2966 -0.2521 -0.1259 3.254
Coefficients: estimate standard z value p value error (Intercept) -3.616e+00 2.192e-01 -16.495 p < 0.0001 PC1 (commenting 2.616e-02 2.995e-03 8.735 p < 0.0001 behaviour) PC2 1.245e-01 3.706e-02 3.360 p < 0.001 (inbound/outbound trajectory) PC1:PC2 (interaction) -5.928e-05 7.435e-04 -0.080 p > 0.05
Degrees of freedom: 1252 total; 1249 residual Null deviance: 481.8 Residual deviance: 381.4 Akaike’s information 389.4 criteria (AIC) Table 6.4: Logistic regression model for the factors predicting early adopter status in the early adopter/non-adopter buy x on iTunes dataset.
The results show that PC1 and PC2 are statistically significant predictors of early adopter status. However, the interaction between the two variables is not determined to be a statistically significant predictor in this case. A Tjur's R2 test, however, shows that the model is a relatively weak fit at predicting early adopter status, with an R2 score of 0.13 (where a score of 1 would have meant that the model was a perfect fit). PC1 and PC2, then, are significant predictors of early adopter status, but the level of prediction that they give is relatively small.
Conclusion
To summarise, this section was concerned with the extent to which the weak-tie theory of language change is applicable to online CofPs. Firstly, I concluded that, unlike in the previous case study, the innovator of buy x on iTunes,
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weak-tie theory of language change's prediction that linguistic innovators would be peripheral members cannot be supported in this case study. Secondly, I found that there was some evidence to support the hypothesis that the influential early adopters in a CofP would be high-status members. 'Months remaining', 'submissions contributed', 'comments contributed', and 'replies received' were, as in the delete it fat case study, all status markers that the majority of early adopters scored higher than the community median on. However, as also observed in the previous case study, other status markers (such as 'one-link ties formed', 'ten-link ties formed', 'month active', 'median score received', and 'moderator status') did not seem to correlate with early adopter status. PCA and logistic regression were subsequently employed to determine which (if any) of the status markers were statistically significant predictors of early adopter status. I conclude that PC1 (commenting behaviour) and PC2 (inbound/outbound trajectory) are both significant predictors of early adopter status, with early adopters tending to score higher on these measures. However, unlike in the delete it fat case study, there is no statistically significant interaction between PC1 and PC2.
Status, hierarchy, power, and the buy x on iTunes LCM policy
This section explores the relationship between hierarchy, status, and power in the Popheads CofP through an exploration of the discourses surrounding the buy x on iTunes endogenous LCM policy. Specifically, I focus on issues of hierarchy, status, and power relating to the advocation, implementation, and effectiveness of the policy.
Advocation for the LCM policy
In the delete it fat case study, this research showed that in the months preceding the ban a small but vocal group of high-status community members had become frustrated with the perceived ubiquity of the form in the Popheads community. These members were consequently considered to be influential in the eventual introduction of the delete it fat LCM policy. In contrast, there was only one recorded expression of negativity towards buy x on iTunes in the Popheads community before the LCM policy was introduced, and it was 156
focused on the form's usage in a different community altogether. Specifically, in October 2016, the following conversation took place after the moderator
1 (22)
In response to
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delete it fat in the months preceding the ban. Furthermore, it seems highly unlikely that this complaint would be influential in the moderators' decision to include buy x on iTunes alongside delete it fat on the LCM policy that they introduced in January 2017. In the delete it fat case study, I concluded that the moderators had chosen a top-down LCM policy that only they could control and enforce. Nevertheless, the findings suggested that the decision to introduce the LMC policy in the first place may have been influenced by complaints about the expression from non-moderating members who scored highly on status hierarchies unrelated to moderation. The present case study differs significantly, as there is no evidence that this specific act of content moderation was advocated for, or even necessarily encouraged, by other members of the community. Indeed, as documented in Section 6.2, there is strong evidence that buy x on iTunes was not only salient to the linguistic repertoire of the community but was also an important contributor towards community identity. Therefore, the ban itself is more of a top-down display of power than encountered previously.
Implementation of the LCM policy
On 1st January 2017, the moderators officially announced that buy x on iTunes, alongside delete it fat, was banned in the community and that comments containing the form would be removed by the moderators and result in warnings or bans for repeated violators (
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In a conversation that took place on the same day as the ban,
1 (23)
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Effectiveness of the LCM policy
In terms of the effectiveness of the ban, the form was not eliminated from the linguistic repertoire of the community, and it continued to diffuse throughout the data collection period.
80
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30 Frequency
20
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0
Jul-16 Jul-17
Jan-17 Jan-18
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Oct-16 Oct-17
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Aug-16 Aug-17
Nov-16 Nov-17
Mar-16 Mar-17 Mar-18
May-16 May-17 May-18
Normalised frequency (per million words) Raw frequency
Figure 6.9: Raw and normalised frequency of buy x on iTunes in the Popheads corpus.
In the immediate aftermath of the ban, however, the frequency of the form did decrease dramatically: usage dropped by over 85% in January when compared with the previous month (there were just ten usages in January 2017). However, summer 2017 saw somewhat of a resurgence in buy x on iTunes usage, with the raw frequency even being as high in September 2017 as it was in the month before the ban (see Figure 6.9). Nevertheless, the relative frequency of the form remained much lower than it was before the introduction of the LCM policy. Therefore, this research concludes that the ban was effective at reducing the frequency of buy x on iTunes both in the short-term and the long-term. However, it was not successful at eliminating the expression from the community. In the delete it fat case study, I showed that in the immediate aftermath of the ban members used the banned expression (and variations thereof) in a subversive way that challenged the power of the moderators. A similar (although less widespread) phenomenon occurred with buy x on iTunes: members posted low-level subversive comments which were arguably intended, in part, to gently undermine or challenge the authority of the moderators. Consider the following conversation which took place in the thread announcing the ban:
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1 (24)
In lines 1-4,
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spaced characters in the word J U S T to reinforce how little time had passed since the ban, indicates that he felt it was important to highlight that the comment was a violation of the LCM policy.
(25)
Here,
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therefore, subversive as it facilitates the breaking of the rules in a way that protects the violator. Similarly, in a post celebrating the moderator
(26)
(27)
This discussion occurred the day after the ban in a thread announcing the best posts on Popheads circa 2016.
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The emphasis is not placed on him having broken the rules of the community or on the possibility of other members being annoyed at the usage. It is the moderators (and the moderators alone) that are positioned as having a problem with the comment. This fits with the findings above that there were no complaints from users about this form before the LCM policy was introduced. Moreover, it also suggests that the moderators' LCM policy is perceived by some users as being based on the language that they personally do not like, as opposed to reflecting the views and preferences of the community the moderators represent.
(28)
(29)
In these replies, the moderators do not chastise
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30%
25%
20% violators 15%
10% Percentage Percentage of
5%
0% 0 1 2 3 4 5 6 7 8 Number of status markers
Figure 6.10: The number of status markers on which the violators of the buy x on iTunes LCM policy score higher than the community median.
Figure 6.10 shows that 97.8% of the members who had the type of power associated with taking back control of their lexicon, had at least one status marker higher than the community median. This is a slight decrease from the 100% in the delete it fat case study but is still, nevertheless, an impressive figure. 83.8% had at least three status markers higher than the community median (a number comparable to the 83% in delete it fat), and 56.3% of early adopters had at least five status markers higher than the median (a slight increase on the 45.2% in the previous case study).
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Meanwhile, Figure 6.11 provides an overview of the most frequently observed high- status markers among the LCM violators. In the delete it fat case study, 'comments contributed', 'submissions contributed', and 'replies received' were found to be status markers that the majority of violators scored higher than the community median on, and these results are replicated here. Here, 93.7% of violators of the buy x on iTunes policy score higher than the community median for 'comments contributed', 72.5% for 'submissions contributed', and 64.9% for 'replies received'. Moreover, this time, 'median score received' is also a relevant factor, with 59.5% of violators scoring highly for this variable. Meanwhile, 'ten-link ties formed' (45%), 'one-link ties formed' (42.8%), 'months active' (37.9%), and 'months remaining' (24.8%) do not appear to be status markers on which the majority of LCM violators score highly. Overall, then, the members who reclaim the right to use the banned form tend to be prolific contributors of both comments and submissions, whose posts receive more replies and higher scores then excepted.
100%
90%
80%
70%
60% violators 50%
40%
30% Percentage Percentage of 20%
10%
0% Comments Submissions Replies Median Ten-link ties One-link ties Months Months contributed contributed received score formed formed active remaining received Figure 6.11: The status markers on which violators of the buy x on iTunes LCM policy score higher than the community median.
The final status marker considered is 'moderator status'. In the delete it fat case study, it was found that the LCM policy had been violated fourteen times by seven moderators (meaning moderators accounted for 5.2% of all violations). Similarly, in this case study, moderators accounted for 6.33% of the violations, with the ban being flouted thirty-three
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times by nine of the twenty-nine (31%) moderators who were active during the period after the ban. One of the most notable moderator violations occurred in May 2017 after a Popheads member reported a post by
(30)
Here,
Conclusion
To conclude this section on status, hierarchy, power, and the buy x on iTunes LCM policy, this case study differed notably from the previous one as no members expressed negative attitudes about the form before it was banned in the CofP. This finding suggests that the moderators acted independently to ban a form that was not troubling any non-moderating members of the community. Indeed, this chapter opened by arguing that buy x on iTunes was not only salient to the linguistic repertoire of the community but was also recognised by
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members as an important aspect of their community identity. The decision to ban buy x on iTunes was seemingly a top-down decision that was not influenced by anyone outside of the moderators' sphere of power. The LCM policy was introduced in January 2017 and caused some members, most notably
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7 Chapter 7: Case study 3 – wig
Introduction
The third case study centres on wig, a word which can be used alone or in creative multiword expressions to indicate that someone is, or will be, surprised and impressed. Typical usages include:
(1)
Chapter 7 will first outline the hypothesised origins of wig and describe how the form (and its variants) are defined and used in the Popheads community. I will then use the case study of wig to explore the applicability of the weak-tie theory of language change to an online CofP. The final section explores the relationship between status, hierarchy, and power through an exploration of the advocation, implementation, and effectiveness of the wig LCM policy.
Community usage
There is no definitive origin for this innovative sense of the word wig. However, a popular and plausible folk etymology (Gehring 2018; Know Your Meme 2018; McDowelle 2018; Shakeri 2018) is that wig originated in African American LGBT+ culture in the expression my wig has been snatched (which, in turn, is hypothesised to be a variant of the expression my weave has been snatched). More specifically, it is believed that this sense originated in the drag ball culture of the 1980s and 1990s, in which (primarily) African American and
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Latino members of the LGBT+ community would compete in a series of events at a masquerade ball involving lip-synching, modelling, and voguing (a form of dancing). In recent years, the word has come to be used relatively widely on social media and particularly in fandom cultures, having been popularised by the American television series RuPaul's Drag Race (2009-) which brought elements of drag ball culture to mainstream attention. This places wig in the tradition of African American Vernacular English (AAVE) forms which have become popular after being adopted by social media users (see Grieve, Nini & Guo 2017; Ilbury 2020). Members of the Popheads community have offered the following definitions of this sense of wig (typically in response to queries from newcomers who express confusion about terminology used in the community):
(4) < JamErectGoobleQuayle>: It's just a super slang-y way of saying you're blown away. As in, you are so blown away/impressed/hyped that your metaphorical wig has been snatched right off your head. (01/03/2017 17:31, 10) (5)
These definitions indicate that the community is broadly in agreement about the meaning of wig: specifically, it is used to positively react to something which is regarded as highly impressive. Furthermore,
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this thesis, given the likely origins of the word in drag culture and also the LGBT+ orientated nature of the subreddit (see Section 4.5) it is unsurprising that, to some members at least, the word indexes the performance of a gay identity. The prototypical usage of wig sees the word appearing in the expression my wig has been snatched or close variations thereof:
(7)
From this starting point, the metaphor can be creatively manipulated in a variety of ways. For instance, the word wig can be detached from the rest of the multiword expression and used as a standalone construction. To exemplify, in April 2016, the following comment was posted in a discussion about a new Beyoncé documentary:
(10)
(11)
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Perhaps as a natural extension of the concept of flight being introduced, members also began describing how far away from their heads their wigs have travelled:
(14)
In the above examples, galactic distances (out of the milky way, into orbit, out of the solar system, out of the galaxy) are used to metaphorically convey the strength of the users' emotions about the thing or person being discussed. The further away their wig is, the more impressed they are. It is clear from the cursory overview above that wig is a major locus for language creativity in the Popheads community. Moreover, it is also important to note that instances of language creativity are also encouraged and praised in the community. For instance, in October 2017,
(19)
In reply,
(20)
Similarly, after
(21)
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Here then we have instances where Popheads members provide positive meta-linguistic commentary on other members' creative manipulations of the wig form, a phenomenon which may serve as positive reinforcement and encourage the proliferation of wig-related language creativity. Although the etymological discussion above served to highlight that wig is not unique to Popheads members, it is nevertheless especially salient to their community identity. To exemplify, in a July 2017 thread entitled "What is the origin of all the shit that's said here?" (
(22)
In the meta-discussions of wig here, the form is not only an important part of the community's lexicon – their shared repertoire – but their language is beloved by them. Wig is something that they "live for" (22), "fuckin' love" (23), and which brings them joy (24).
The weak-tie theory of language change
The innovator
The first usage of wig in the Popheads corpus occurred two months into the community's lifespan, when
174
(25)
In this usage,
Author
Table 7.1: Status markers for
Table 7.1 shows that
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no ten-link ties at this point in time). The only status marker that
The early adopters
Between its introduction in October 2015 and the end of February 2017, wig was used by just 65 members of the community (Figure 7.1). However, in March 2017, the diffusion of wig began in earnest: the number of users increased from 65 at the end of February to 97 by the end of March 2017 (an increase of 39.5% in just one month). The early adopters, then, are defined here as the 64 people who used wig between its introduction by
800
700
600
500
400
300 Numberusers of
200
100
0
Figure 7.1: Cumulative number of users of wig.
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In order to explore if the weak-tie theory of language change's prediction about early adopters held in this community, I first analysed the percentage of early adopters of wig that fell above, at, or below the community median for each of the eight quantitative status markers. I also calculated the percentage of early adopters that were part of the moderating team at the time of uptake.
100% 90% 80% 70% 60% 50% 40% 30%
20% Percentage Percentage of earlyadopters 10% 0% months months submissions comments replies one-link ties ten-link ties median active remaining contributed contributed received formed formed score received
Below the median At the median Above the median
Figure 7.2: Percentage of early adopters of wig who scored above, at, or below the community median for the quantitative status markers.
Months Active Just 35.9% of early adopters of wig had been active in the community for longer than the community median time at the point of uptake (a number comparable to the 34.3% and 33.3% in the delete it fat and buy x on iTunes case studies). However, this number, again, reflects the fact that the community median for months active was high during most of the wig early adoption period. Table 7.2 confirms that just 14.1% of early adopters had been active for less than three months, with 85.4% having been in the community for at least four months at the time of uptake.
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Months active Percentage of early adopters 1 - 3 months 14.1% 4 - 11 months 62.5% 12 months + 23.4%
Table 7.2: Number of months that early adopters of wig had been active at the time of uptake.
Months remaining Figure 7.2 demonstrates that 60.9% of early adopters of wig remain in the community for longer than the community median time after the point of early adoption, representing a slight decrease from the 71.4% and 65% in the delete it fat and buy x on iTunes case studies. Nevertheless, Table 7.3 shows that just 10.9% of early adopters left Popheads in the three months following their uptake, 89.1% remained for at least another four months, and 75% for over a year.
Months remaining Percentage of early adopters 0 - 3 months 10.9% 4 - 11 months 14.1% 12 months + 75%
Table 7.3: Number of months that early adopters of wig remained active after the time of uptake.
Submissions contributed The findings show that 57.8% of early adopters of wig contributed more submissions than the community median. Although this number means that the majority of early adopters score highly for this marker, it nevertheless represents a notable decrease from the 85.7% and 86.7% who scored higher than the community median for 'submissions contributed' in the delete it fat and buy x on iTunes case studies.
Comments contributed Figure 7.2 shows that 79.7% of early adopters scored higher for comments contributed than the community median. Again, although this percentage signifies that the majority of early adopters are ranked high in the hierarchy for this measure, it is nevertheless lower than the percentages in the delete it fat and buy x on iTunes case studies (where the numbers were 88.6% and 96.7%, respectively).
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Replies received The findings above demonstrate that 59.38% of wig early adopters received more replies than the community median, a number which is slightly lower than the 77.1% and 66.7% in the delete it fat and buy x on iTunes case studies.
One-link ties formed The delete it fat and buy x on iTunes case studies showed that while approximately 50% of early adopters had formed more one-link ties than the community median, approximately 50% had formed fewer one-link ties. In these case studies then, I concluded that there did not seem to be a correlation between one-link ties formed and early adoption. The early adopters of wig, however, break this pattern, but not in the way that one would necessarily predict. There appears to be a negative correlation between early adopters of wig and the number of one-link ties formed. Just 34.4% of early adopters had formed more one-link ties than the community median, while the majority (65.6%) scored lower than the median for this measure. Nevertheless, what is consistent across all three case studies is that high scores on this measure do not correlate with early adopter status.
Ten-link ties formed Similarly, high scores on the 'ten-link ties formed' variable, again, do not seem to correlate with early adopter status. Figure 7.2 shows that just 42.19% of early adopters had formed more ten-link ties than the community median (which means that they had formed at least one), while the larger percentage (57.8%) had formed a number of ties equal to the community median (which was zero throughout the early adoption period for wig).
Median score received The findings show that 50% of early adopters received higher scores on their posts than the community median, another 35.9% received scores which were in line with the median, and 14.1% had a score lower the median. These findings, which do not suggest a notable relationship between this measure and early adoption, are congruent with those in the delete it fat and buy x on iTunes case studies.
Moderators
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The previous case studies both concluded that two early adopters of the forms studied were members of the moderating team at the time of uptake. In contrast, no moderators were early adopters of wig.
Overall, then, this exploration of the status markers for early adopters of wig concurs with the previous two case studies, which found that there were four status markers on which the early adopters tend to score higher than the community median ('months remaining' 'comments contributed', 'submissions contributed', and 'replies received'). However, it is worth noting that, here, the percentage of members who score higher than the community median is much lower across all four measures than seen in the previous case studies. As also observed in the delete it fat and buy x on iTunes case studies, it seems to be the case that high scores on the other five status markers ('months active', 'one-link ties formed', 'ten-link ties formed', 'median score received', and 'moderator status') do not correlate with early adopter status. To summarise, there is tentative support here for the idea that early adopters are high- status members of the community, as predicted by the weak-tie theory of language change. However, the relationship between early adoption and status is clearly more complex than is captured in the statement above, with, for instance, some status markers having no relationship with early adoption and also relatively large percentages of early adopters deviating from the generally observed patterns among the rest of their early adopter peers. Therefore, to investigate this relationship further, I performed a PCA and logistic regression to identify the status markers that were statistically significant predictors of early adopters of wig. Here, the status markers for the sixty-four early adopters of wig were compared with the status markers for their 1,681 non-adopting counterparts. First, however, a preliminary Spearman correlation analysis determined that there were no strong relationships between variables in the early adopter/non-adopter wig dataset (Figure 7.3): the strongest correlation had a Spearman correlation coefficient of 0.56 (a value of 0.7+ signifies a strong correlation).
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Figure 7.3: Correlation matrix for the early adopter/non-adopter wig dataset.
The PCA findings (Figure 7.4) showed that ten principal components (PCs) collectively account for most of the variance in the dataset. This research examines the two PCs which explain the highest proportion of the variance, plus (if applicable) any additional PCs which explain 5% of the variance or more. However, as with the previous case studies, PC3 – PC10 individually account for less than 5% of the variance of the dataset and are thus not analysed further.
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100% 93.78% 90%
80%
70%
60%
50%
40%
Proportion of variance 30%
20%
10% 3.17% 1.97% 0.55% 0.34% 0.20% 0.00% 0.00% 0.00% 0.00% 0% PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 Figure 7.4: The proportion of variance accounted for by the principal components identified in the early adopter/non-adopter wig dataset.
Figure 7.4 shows that PC1 accounts for 93.78% of the variance in the dataset. An examination of the loadings for PC1 (Figure 7.5) shows that 'comments contributed' is the largest contributing factor to this PC. This finding is congruent with those in the previous case studies. PC1 is thus, again, referred to as a measure of 'commenting behaviour'.
Comments contributed 1.00
Submissions contributed 0.03
Months remaining 0.03
Early adopter status 0.00
Replies received 0.00
Moderator status 0.00
Median score received 0.00
Ten-link ties formed 0.00
One-link ties formed 0.00
Months active -0.01
-0.20 0.00 0.20 0.40 0.60 0.80 1.00 Loadings score
Figure 7.5: Loadings for PC1 in the early adopter/non-adopter wig dataset.
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Figure 7.4 illustrates that PC2 amounts for a relatively small amount of the variance in the dataset (3.17%). The loadings in Figure 7.6 show that PC2 is primarily a combination of months remaining and, to a lesser extent, months active, a finding which is consistent with the other case studies where PC2 was labelled 'inbound/outbound trajectory'.
Months remaining 0.92
Months active 0.40
Median score received 0.03
Early adopter status 0.00
Replies received 0.00
Moderator status 0.00
Ten-link ties formed 0.00
One-link ties formed 0.00
Submissions contributed -0.01
Comments contributed -0.02
-0.20 0.00 0.20 0.40 0.60 0.80 1.00 Loadings score
Figure 7.6: Loadings for PC2 in the early adopter/non-adopter wig dataset.
Overall, then, 96.95% of the variance in the wig early adopter vs non-adopter dataset can be explained by two variables: PC1 (commenting behaviour) and PC2 (inbound/outbound trajectory). Figure 7.7, below, demonstrates the scores for each of the early adopters and non- adopters of wig across these two variables. Figure 7.8 is a simplified version of the same graph, with the extreme values removed to enable better visualisation of the key findings.
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Figure 7.7: Plot showing scores on PC1 and PC2 for members included in the early adopter/non- adopter wig dataset.
Figure 7.8: Simplified plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter wig dataset.
The patterns observed here are very similar to those in the previous case studies. In terms of PC1, 87% of non-adopters are clustered around the -15 to 0 points on the x-axis, indicating that they contributed relatively few comments to the Popheads community.
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Meanwhile, although 42% of early adopters cluster around the -15 to 0 points, 58% score positively on this axis, indicating a higher degree of commenting prolificness for the majority of this group. In terms of PC2, 38.8% of non-adopters score negatively for this measure (suggesting they were on outbound trajectories), while 61.2% score positively. Meanwhile, a much higher 78.12% of early adopters score positively on this variable, indicating that early adopters are consistently more likely to be on inbound trajectories. There once again appears to be an interaction between PC1 and PC2 of the kind observed in the delete it fat case study. Specifically, the majority of both non-adopters and early adopters regularly score positively on PC2 (61.27% and 78.12% respectively). However, of the 1,030 non-adopters who score positively for PC2, only 206 (20%) also score positively for PC1. In contrast, of the 50 early adopters who score positively for PC2, 32 (64%) also score positively for PC1. Therefore, it would seem that high scores on both PC1 and PC2 may serve as a predictor of early adopter status. To determine the significance of the patterns identified above, a logistic regression was performed (Table 7.4). The results show that PC1, PC2, and an interaction between these two variables are all statistically significant predictors of early adopter status. However, a Tjur's R2 test (which assesses the predictability of the logistic regression model) shows that the model is an extremely weak fit at predicting adopter status, with an R2 score of just 0.06.
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Input (early adopter) 0.037 Total N 1745
Deviance residuals: Min 1Q Median 3Q Max -1.4662 -0.2616 -0.2369 -0.1773 3.0060
Coefficients: estimate standard z value p value error (Intercept) -3.5652978 0.1569164 -22.721 p < 0.0001 PC1 (commenting 0.0141776 0.0020118 7.047 p < 0.0001 behaviour) PC2 0.0764716 0.0273663 2.794 p < 0.01 (inbound/outbound trajectory) PC1:PC2 (interaction) 0.0010868 0.0005129 2.119 p < 0.05
Degrees of freedom: 1744 total; 1741 residual Null deviance: 548.7 Residual deviance: 484.8 Akaike’s information 492.8 criteria (AIC) Table 7.4: Logistic regression model for the factors predicting early adopter status in the early adopter/non-adopter wig dataset.
Conclusion
To summarise, this section explored the extent to which the weak-tie theory of language change is applicable to an online CofP by looking at the status markers for the innovator and early adopters of wig. In terms of the innovator, I concluded that
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received', and 'moderator status') did not seem to correlate with early adopter status. This finding further supports the idea that the relationship between early adoption and status is not necessarily straightforward. Consequently, PCA and logistic regression were employed to determine which status markers serve as statistically significant predictors of early adopter status. This research determined that both PC1 (commenting behaviour) and PC2 (inbound/outbound trajectory) were statistically significant predictors of early adopter status. Moreover, as found in the delete it fat case study (but not the buy x on iTunes research), there was also a statistically significant multidimensional interaction between PC1 and PC2.
Status, hierarchy, power, and the wig LCM policy
This section explores the relationship between hierarchy, status, and power in the Popheads CofP through an exploration of the discourses surrounding the wig LCM policy. Specifically, I focus on issues of hierarchy, status, and power relating to the advocation, implementation, and effectiveness of the policy.
Advocation for the LCM policy
The first recorded complaint about wig was posted at the end of April 2017 (as wig was rapidly diffusing through the community) by a newcomer to the community,
(26)
Although we can perhaps reasonably assume that
more established member,
1 (27)
After
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here that it was the forms listed by
189
about recurring "petty arguments" in threads about the American girl band Fifth Harmony, the following conversation took place:
1 (28)
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marker "please" (Bunz & Campbell 2004). As with
(29)
Here
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In reply to
(30)
Importantly,
(31)
In addition to
1 (33)
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6 we had an old rule in discussion threads to never just post the song title and nothing 7 else but 60% of the subreddit refused to listen and continued breaking that rule 8 anyway. it was just too hard to enforce so i pretty much gave up on trying to.
9 we love a good quality post! and we love a good quality comment! but a happy 10 medium is something i love just as much and some of these complaints could be 11 easily solved if users sometimes added more to the discussion with what they 12 commented. 13 thank you, though, for letting us know your thoughts. <3 (10/02/2018 02:41, 1)
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Later, in the same Town Hall discussion thread, another two users also advocate that wig be banned:
(34)
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that the nine users who complained about wig from January 2018 onwards may have influenced the moderators' decision to add the form to the LCM policy (as evidenced, for instance, by the moderators' responses and direct engagement with a number of these posts). In Table 7.5 below, I compare the status markers for the nine users at the time that they expressed negative opinions about wig to the community medians for the status markers at that time (with the latter given in parentheses). All nine members whose complaints about wig seemed to be influential in its banning score higher than the community median for at least one status marker, while six of the nine score higher for at least five of the status markers. 'Comments contributed' is the status marker shared by the greatest majority of these members, with eight of the nine scoring higher than the median on this marker. Meanwhile, seven of the nine had been active in the community for longer than the median time, six of the nine had received more replies and formed more ten-link ties than the community median, and five of the nine had a higher median score on their posts than expected. In contrast, 'submissions contributed' and 'one-link ties formed' are status markers shared by a smaller proportion of these members, with only four of the nine scoring higher than the median for these markers. Meanwhile, none of the users who seemed to be influential in petitioning for the banning of wig scored higher than the community median for 'months remaining'. Nevertheless, the latter finding must be considered in light of the fact that seven of the nine members actually remained in the community until the end of the data collection period but are not considered to score highly for 'months remaining' because this was typical for full members at that point in time. Some of these findings are in line with those from the delete it fat case study. Specifically, that case study also concluded that all of the members studied scored higher than the community median for at least one status marker (in fact, all four scored higher than the community median for at least four status markers). Moreover, the delete it fat study too found that 'comments contributed', 'replies received', and 'ten-link ties formed' were status markers on which most of the sample scored highly, while scores for 'one-link ties' were not high for most. On the other hand, the majority of the members who complained about delete it fat scored highly for 'months remaining and 'submissions contributed', neither of which were notable status markers here. Additionally, this study found that 'median score received' and 'months active' were relevant status markers for the LCM advocates, while the delete it fat case study did not support this finding. 195
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To summarise, prior to the introduction of the wig LCM policy in May 2018, thirteen different members complained about the form. Four of these complaints occurred too early to be realistically deemed influential in its eventual banning. However, the remaining nine are hypothesised to have potentially been influential in the introduction of the LCM policy. These nine users all scored higher than the community median for at least one status marker, which supports the tentative conclusion reached in the delete it fat case study that there might be a correlation between high rankings in the non-moderator status hierarchies – such as 'comments contributed' and 'ten-link ties formed' – and the power to influence the moderators' decision-making process with regards to LCM in the Popheads CofP.
Implementation of the LCM policy
On 2nd May 2018, the Popheads moderators banned this innovative sense of wig in the community. In contrast to the lengthy and 'harsh' announcement in January 2017 when the buy x on iTunes and delete it fat LCM policies were introduced, when wig was banned in May 2018, the announcement was much more understated. The announcement formed a small section of a much larger post containing important updates to the community's rules. Instead of announcing the banned forms individually in the post, members were given a hyperlink which took them to the full list of terms covered by the LCM policy in the community. The moderators did not want to "create a wall of text nobody will read" (as there were a relatively large number of forms that fell under the policy by this point) in the main announcement post (
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Overall, then, this post represented a markedly different tone to the one used in the January 2017 announcement. It seems reasonable to conclude that, because LCM was an established practice in the Popheads community by May 2018, the moderators did not need to demonstrate a strong top-down force of authority and power to embed the rules into the CofP's shared repertoire. The banning of wig was more a case of updating a policy to add another form, rather than 'forcing' LCM onto the community. Additionally, another important facet to consider is that the January 2017 post was made by
Effectiveness of the LCM policy
As discussed in Section 5.4.3, it is very difficult to retrospectively retrieve the content of removed posts, so it is not possible to determine if the moderators removed any posts for using wig after the ban. Nevertheless, there is no explicit textual evidence in the corpus to indicate that any posts were removed for containing the form. Furthermore, in contrast to the findings of the delete it fat and buy x on iTunes case studies, this time there is no evidence that any moderators publicly chastised users for violating the LCM policy relating to wig. Although, interestingly,
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Figure 7.9 shows the raw and normalised frequencies of wig in the Popheads corpus from its first usage in October 2015 until the end of the data collection period in May 2018.
300
250
200
150 Frequency 100
50
0
Normalised frequency (per million words) Raw frequency
Figure 7.9: Raw and normalised frequency of wig in the Popheads corpus.
The previous case studies concluded that while the LCM policies failed to eliminate the banned forms from the community, they were nevertheless effective at reducing their frequencies both from a short and long-term perspective. Wig was banned at the start of May 2018 and the data collection period finished at the end of that month: this means that there is no longitudinal data available to study the long-term effects of the ban. In terms of the short- term effects, a cursory glance at Figure 7.9 demonstrates that the normalised frequency of wig decreased markedly in May 2018 following the ban. The form had been used 165.9 times PMW in April 2018, and this number dropped to 95.3 times PMW in May 2018. However, when taking a broader perspective and considering the frequency of the form in February and March 2018 (where it was used 86.5 times PMW and 110.2 times PMW, respectively), these numbers are very similar to the 95.3 times PMW frequency in May 2018. In other words, then, it is not clear if there really was a decline in frequency following the LCM policy or if the usage in the month before the ban was just abnormally high (indeed, April 2018 saw the highest normalised frequency for this form recorded in the corpus). Figure 7.10 below shows the daily normalised frequency of wig in the Popheads corpus from 1st January until 30th May
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2018. The markers in orange represent daily usages once the ban was in place (that is, from 2nd May 2018 until the end of data collection on 31st May).5
600
500
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300 Frequency 200
100
0 0 20 40 60 80 100 120 140 160
Before the ban After the ban
Figure 7.10: Daily normalised frequency (per million words) of wig in the Popheads corpus (1st January 2018 - 31st May 2018).
Overall, there is no notable decrease in daily frequency following the announcement that wig was banned on 2nd May 2018. A Spearman correlation test on the normalised frequency of wig between 1st Jan 2018 and 31st May 2018 returned a value of -0.105. This result indicates that wig did decrease slightly in frequency across 2018, but the decrease is so weak that it is unremarkable. There are two key reasons why the wig LCM policy may have been unsuccessful. Firstly, as above, members know that LCM policy violation is a relatively common practice in the community and seemingly not something which will lead to terrible consequences (as was the fear among some members back in January 2017 when the buy x on iTunes policy was introduced). Secondly, the form may have been too deeply embedded in the community by May 2018 to be successfully reduced in frequency. All forms considered in this work are highly important to the community and are considered by members to be salient aspects of the community's linguistic repertoire. However, delete it fat was banned just two months after the end of its early adoption period (that is, when diffusion was beginning in earnest) and buy
5 Excluded here are instances of wig used in the reviews in ‘rate’ threads as it is impossible to know if the reviews were penned and submitted before or after the ban 200
x on iTunes just one month after the end of early adoption. In other words, then, these forms had not been in widespread use in the community for a very long time before LCM was introduced. In contrast, fourteen months had passed between the end of the wig early adoption period and the introduction of the LCM policy: the form had time to become embedded in the community and become a familiar part of the community's lexicon. In total, excluding usages in rate reviews that could have been written before the ban, there were 131 verifiable usages of wig from ninety-four members in May 2018 after the ban was announced, suggesting that
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25%
20%
15% violators
10% Percentage Percentage of 5%
0% 0 1 2 3 4 5 6 7 Number of status markers
Figure 7.11: The number of status markers on which the violators of the wig LCM policy score higher than the community median.
Figure 7.12 shows that 'comments contributed' was the status marker on which the vast majority (86.2%) of LCM violators scored higher than the median, followed by 'submissions contributed' (67%), and 'median score received' (58.5%). These three status markers have all been linked to LCM violators in at least one of the other case studies. Although high scores on 'replies received' seemed to correlate with LCM violation in the delete it fat and buy x on iTunes case studies, here the majority of violators do not score highly on this measure. Additionally, in a finding which is congruent with the other case studies, high scores on 'months active', 'one-link ties formed', and 'ten-link ties formed' do not seem to correlate with violators of the ban. Finally, as explained above, 'months remaining was a variable that could not be studied in this instance because of the lack of longitudinal data.
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100
90
80
70
60 violators 50
40
30 Percentage Percentage of 20
10
0 Comments Submissions Median Months Replies One-link ties Ten-link ties Months contributed contributed score active received formed formed remaining received Figure 7.12: The status markers on which violators of the wig LCM policy score higher than the community median.
The final variable explored in relation to the LCM violators is 'moderator status'. In the delete it fat case study, seven moderators were found to have violated the LCM policy fourteen times, accounting for 5.2% of all violations. Meanwhile, the nine moderators who violated the buy x on iTunes LCM policy a total of thirty-three times accounted for 6.3% of all violations. In this case study, there are four violations from three moderators (representing 15% of the active moderating team), which account for 3.1% of the violations recorded. However, it is also worth considering that the violations documented in the previous two case studies occurred over seventeen months, with the vast majority taking place several months after the ban was announced. Here, however, only violations over a period of one month are documented. In other words, it is difficult to make comparisons between the findings here and the more longitudinal findings in the previous chapters. It may have been the case, for instance, that more moderators would violate the LCM policy when a longer time had passed since the ban's announcement.
Conclusion
To summarise, the findings of the investigation into the relationship between status, hierarchy, power, and the wig LCM policy variably support and expand on the conclusions reached in the previous two chapters.
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In terms of advocation for the ban, Chapter 5 concluded that a small number of members who scored highly on several status markers seemed to be influential in the decision to introduce the delete it fat LCM policy. This time, however, we see multiple non- moderating members explicitly attempting to influence the moderators to add the wig form to the LCM policy in the lead up to the May 2018 ban. The members who are hypothesised to have been successful in their attempts to influence the decision all score highly on at least one status marker. In the previous two case studies, the analysis explored processes of both low-level and explicit subversion of the LCM policies, as members employed a range of linguistic and discursive strategies to rebel against and challenge the delete it fat and buy x on iTunes ban. In the wig case study, however, there is no comparable backlash or rebellion following the introduction of the LCM policy. I hypothesised that reasons for this might include the markedly less authoritative tone used to introduce the wig LCM policy, the fact that LCM was an established and normalised part of the community's repertoire by May 2018, and also the fact that members know that the LCM policies are frequency violated, even by the moderators themselves. A full overview of the effectiveness of the wig LCM policy was not possible because of the lack of longitudinal data. However, even from a short-term perspective, there is little conclusive evidence to suggest that the ban was successful. I suggest that this may have been the case both because members know that violations of LCM policies are commonplace in the community and also because the word had become too firmly entrenched over time in the community's linguistic repertoire. The analysis showed that 96.8% of the violators of the wig LCM policy score higher than the community median on at least one status marker, 75% score higher on at least three, and 42.5% on at least five. The violators of the policy tended to be prolific contributors of both comments and submissions, whose posts received higher scores than expected. Overall, then, there is support for the idea that the power associated with rebelling against LCM is linked to high scores on several hierarchies unrelated to moderator status.
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8 Chapter 8: Case study 4 – tea
Introduction
The fourth and final case study explored in this thesis focuses on the innovation tea and its formal variants. The semantic complexities of the word will be discussed shortly, but, broadly, the word can be glossed as 'truth' or 'gossip' as in the following concordance lines:
(1)
Chapter 8 will first consider the origins of the word and its usage in the Popheads community, before turning to look at the extent to which the profiles of the innovator and early adopters of this form were consistent with the predictions of the weak-tie theory of language change. Tea was not banned in the community until July 2018 (which was after the end of the data collection period), so this case study cannot be used to further explore the relationship between status, hierarchy, and power in the Popheads CofP.
Community usage
Tea, similarly to wig, is believed to have its origins in African American culture. In Hawkeswood's 1980s ethnographic research, his gay African American participants living in Harlem, New York defined tea as 'gossip' (Hawkeswood & Costley 2003). His participants indicated that it was a lexical item associated with AAVE in the southern states of America. Hawkeswood wrote: "three southern-born informants explained 'tea' as 'gossip,' such as that exchanged between 'girls' taking tea in the afternoon" (Hawkeswood & Costley 2003: 210). Similarly, an Urban Dictionary user by the name of Beava Diva posted an entry for this sense of tea in April 2012 which supports this account of the etymological origins of the expression:
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To share gossip. A term started within the gay community of San Antonio, Texas and spread originally throughout the South Central region of the United States. Now used throughout the gay communities in United States and possibly other countries. It comes from the idea of having old Southern tea parties in the South to gossip behind people's back (Beava Diva 2012: n.p.)
Notably, both of these accounts of the origins of tea suggest a metonymic association between tea and the revealing of information: the tea that gossip is shared over becomes the symbolic representation of the discursive act of sharing opinions and speculations. The generally accepted folk etymology for this expression, then, is that it emerged in AAVE in the southern states of America and eventually became widely used within the LGBT+ community. In the 21st century, the word was popularised as drag culture entered the mainstream via shows such as RuPaul's Drag Race, and it is now used widely on social media. Although the form is in relatively widespread usage elsewhere, tea is nevertheless a key part of the Popheads' shared linguistic repertoire, and members regularly cite it as a defining part of the community's lexicon. The traditional definition, in which tea is synonymous with gossip, conforms to many of the usages of tea within the Popheads corpus. Consider the following:
(3)
In (3),
(5)
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(6)
In (5)
1 (7)
In line 3,
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while the latter refers to "objective fact[s]", the former is used in a "shady, gossipy sense". So, tea and truth, in the minds of some members, are not interchangeable terms. Tea is not associated with factual statements, but more "gossipy" opinions. Moreover, the semantic boundaries of tea are further blurred in the Popheads community by a popular type of wordplay where members deliberately draw on the polysemy of the word to ludically merge the truth/gossip sense and the traditional meaning of 'tea' (that is, a hot beverage). Consider the following post:
(8)
In (8) the user
(9) <3cuteFunk>: I have a sore throat, but all that tea really helped (12/02/2017 17:17, 6)
<3cuteFunk> seems to be playing on the polysemy of the word. He is taking the association between the beverage tea and the soothing of a sore throat and then incorporating that into the figurative usage and playfully claiming that the gossip/tea has soothed his sore throat in the same way that a literal cup of tea would. Like all of the other creative forms explored in this thesis, tea became highly salient to the Popheads shared linguistic repertoire in the months following its emergence. For instance, in August 2016, a thread was posted asking Popheads members, "Which slang words in r/pophead's lexicon do you wish would stop, and which are you fond of?" (
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(
The weak-tie theory of language change
The innovator
The first usage of tea occurred one month into the existence of the community in a conversation about the unusual release schedule for the musician Carly Rae Jepsen's third album E•MO•TION:
(10)
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This is the second example of an unsuccessful innovation recorded in this research. In the first example, discussed in Chapter 5, I hypothesised that the innovation might have failed because the innovator was seemingly an aggressive outsider who was engaging in troll-like behaviour. Moreover, the form was used in a comment that was negatively received (scoring -2). However, negative reception is not a relevant factor in the present case study. Moreover, the status markers for the failed innovator,
Author
Table 8.1: Status markers for
Table 8.1 shows that
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joint enterprise which aid in the diffusion and adoption of elements of the shared linguistic repertoire may have still been emerging. The second usage of tea in the Popheads corpus occurred in a discussion about the singer Mariah Carey. The original comment which began the conversation has been deleted. However, one can infer from the reply chain that the author had posted a negative opinion about Mariah Carey, and the exchange below subsequently followed:
(11)
This usage is very close to the standard tea form.
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Author
Table 8.2: Status markers for
As illustrated in Table 8.2, at the time of innovation,
The early adopters
After its successful introduction in February 2016, tea had a slow diffusion process in the Popheads community. Although the word gained new users every month from February 2016 onwards, it was not until June 2017 that the speed of the diffusion process increased, creating
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the sharp uptake in new users associated, in this research, with the end of the early adoption period. Therefore, in this chapter, the early adopters are defined as the 131 members who adopted tea between its introduction in February 2016 and the end of May 2017.
500
450
400
350
300
250
200 Numberusers of 150
100
50
0
Figure 8.1: Cumulative number of users of tea.
To explore if the weak-tie theory of language change's prediction that early adopters would be high-status members holds in this dataset, I first explore how the early adopters score on each measure of status compared to the community median (Figure 8.2):
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100% 90% 80% 70% 60% 50% 40% 30%
20% Percentage Percentage of earlyadopters 10% 0% months months submissions comments replies one-link ties ten-link ties median active remaining contributed contributed received formed formed score received
Below the median At the median Above the median
Figure 8.2: Percentage of early adopters of tea who scored above, at, or below the community median for the quantitative status markers.
Months active Just 35.9% of early adopters of tea had been active for longer than the community median time. This number is entirely in line with the other case studies, which have found between 33.3% and 35.9% of early adopters to have scored higher than the community median for this measure. Table 8.3 illustrates that over 70% of early adopters has been active for four months or longer at the time of uptake, with just 29% being newcomers.
Months active Percentage of early adopters 1 - 3 months 29% 4 - 11 months 49.6% 12 months + 21.4%
Table 8.3: Number of months that early adopters of tea had been active at the time of uptake.
Months remaining The majority (65.7%) of early adopters of tea remain in the community for longer than the community median time after the point of uptake. This finding is consistent with the previous case studies, in which between 60.9% to 71.4% of early adopters were found to be on an inbound trajectory.
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The breakdown of 'months remaining', in Table 8.4, shows that just 9.2% of early adopters of tea leave the community within the first three months of adoption, 90.8% remain for at least four months, and 77.1% remain for at least twelve months.
Months remaining Percentage of early adopters 0 - 3 months 9.2% 4 - 11 months 13.7% 12 months + 77.1%
Table 8.4: Number of months that early adopters of tea remained active after the time of uptake.
Submissions contributed A notable 74.1% of early adopters posted more submissions than the community median. This number is a slight decrease on the 85.7% and 86.7% of early adopters who scored higher than the community median for 'submissions contributed' in the delete it fat and buy x on iTunes case studies, but an increase on the 57.8% who scored higher than the community median in the wig case study.
Comments contributed The vast majority of early adopters were, once again, found to be relatively prolific commenters. Here, 92.5% of early adopters of tea post more comments than the community median, which is the second highest percentage observed for this measure across the case studies (with the highest being the 96.7% in the delete it fat study).
Replies received Figure 8.2 above shows that 65.7% of early adopters receive more replies to their posts than is typical in the community. This finding is congruent with the other case studies, which have found that between 59.4% and 77.1% of early adopters score higher than the community median on this measure.
One-link ties formed The findings once again showed an almost 50/50 split for this measure: 52.7% of early adopters had formed more one-link ties than the community median, while 47.3% had formed fewer ties than the community median. Therefore, in a finding which is consistent with all of
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the other case studies considered here, there does not appear to be a correlation between high scores on the 'one-link ties formed' variable and early adoption.
Ten-link ties formed The findings in Figure 8.2 above show that while 48.85% of early adopters scored above the community median for this measure, 51.15% scored equal to the median (having formed 0 ten-link ties during their time in the community). Therefore, it is once again the case that there is no relationship between high scores on this status measure and early adoption.
Median score received In findings which are consistent with those documented in the previous case studies, there does not appear to be a relationship between 'median score received' and early adoption. In this case study, 45.8% of early adopters score higher than the community median, 38.2% score equal to the median, and 16% less than the median.
Moderators Although no moderators were early adopters of wig, two were included on the list of early adopters for both delete it fat and buy x on iTunes. In this case study, a remarkable seven moderators were among the early adopters of tea. However, these seven represent less than one-third of the twenty-two moderators who were active during the early adoption period. Therefore, moderator status also does not seem to meaningfully correlate with early adopter status.
To summarise, the findings of this case study are concurrent with those in the previous three chapters. Once again, there is tentative support for the hypothesis that early adopters are high-status members of the community. Specifically, high scores on four status markers ('months remaining', 'comments contributed', 'submissions contributed', and 'replies received') seem to correlate with early adopter status. However, the hypothesis is problematised by the five status markers ('months active', 'one-link ties formed', 'ten-link ties formed', 'median score received', and 'moderator status') which seem to have no meaningful correlation with early adopter status. To explore the relationship between early adoption and status further, PCA and logistic regression were performed to identify the status markers which were statistically significant predictors of early adoption of tea. The status markers for the 131 early adopters of tea were 216
compared to the status markers for the 2,254 Popheads members who were active during the early adoption period but did not take up tea. Firstly, however, a Spearman correlation analysis was performed to determine if there were any strong relationships between variables in the dataset. Figure 8.3 illustrates that there are no strong correlations between the variables explored: the strongest correlation has a Spearman correlation coefficient value of 0.58 (where a value of 0.7+ would signify a strong correlation).
Figure 8.3: Correlation matrix for the early adopter/non-adopter tea dataset.
As illustrated in Figure 8.4, the PCA analysis identified ten PCs which collectively accounted for the majority of the variance in the dataset.
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100% 96.10%
90%
80%
70%
60%
50%
40%
Proportion of variance 30%
20%
10% 1.96% 1.30% 0.30% 0.20% 0.14% 0.00% 0.00% 0.00% 0.00% 0% PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Figure 8.4: The proportion of variance accounted for by the principal components identified in the early adopter/non-adopter tea dataset.
The first PC identified (PC1) accounts for 96.1% of the variance in the original dataset. An examination of the loadings for PC1 (Figure 8.5) shows that, as observed consistently across all of the case studies, PC1 is largely synonymous with the 'comments contributed' variable and is thus a measure of 'commenting behaviour'.
Comments contributed 1.00
Submissions contributed 0.03
Months remaining 0.02
Early adopter status 0.00
Median score received 0.00
Moderator status 0.00
Replies received 0.00
Ten-link ties formed 0.00
One-link ties formed 0.00
Months active -0.01
-0.20 0.00 0.20 0.40 0.60 0.80 1.00 Loadings score
Figure 8.5: Loadings for PC1 in the early adopter/non-adopter tea dataset.
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PC2, in this case study, accounts for just 1.96% of the variance in the dataset. 'Months active' and 'months remaining' are, once again, the largest contributing factors towards this PC. However, in this instance, 'months active' is more influential than 'months remaining', which represents a reversal of the pattern observed consistently across the other case studies. Consequently, in this instance, PC2 cannot be considered a variable associated primarily with 'inbound/outbound trajectories', and it will instead be referred to as 'time active in the community'.
Months active 0.93
Months remaining 0.36
Moderator status 0.00
Ten-link ties formed 0.00
Early adopter status 0.00
One-link ties formed 0.00
Submissions contributed 0.00
Comments contributed 0.00
Replies received -0.01
Median score received -0.01
-0.20 0.00 0.20 0.40 0.60 0.80 1.00 Loadings score
Figure 8.6: Loadings for PC2 in the early adopter/non-adopter tea dataset.
Figure 8.7 shows the scores for the early adopters and non-adopters of tea across the PC1 and PC2 variables. Figure 8.8 is a simplified version of the same graph, with the extreme values removed.
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Figure 8.7: Plot showing scores on PC1 and PC2 for members included in the early adopter/non- adopter tea dataset.
Figure 8.8: Simplified plot showing scores on PC1 and PC2 for members included in the early adopter/non-adopter tea dataset.
In terms of PC1 (commenting behaviour), a large percentage (83%) of non-adopters score on the negative side of the x-axis, reflecting a relatively low level of commenting prolificness among this group. In contrast, 71% of early adopters cluster on the positive side
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of the x-axis. This finding reflects an inclination towards commenting prolificness among the early adopters of tea. In the previous case studies, when PC2 was a measure of 'inbound/outbound trajectories', I showed that while non-adopters tended to clustered on both sides of the y-axis, there was a strong preference for early adopters to cluster on the positive side of the axis. However, this pattern differs in the tea case study, where PC2 is now a measure associated with 'time active in the community'. It is still the case that non-adopters cluster on both sides of the y-axis: 53% score less than zero (indicating that they spent less time in the community), while 47% of non-adopters score higher than zero (indicating a greater length of time spent in the community). However, this time, early adopters do not show a tendency to cluster on the positive side of the axis. In fact, 60% have a PC2 score of less than 0 and only 40% more than 0, indicating a weak preference for spending less time in the community before the point of adoption. It is doubtful that, in this study, PC2 would be strongly correlated with early adoption. Similarly, there does not appear to be any notable interactions between PC1 and PC2 in this case study. To further explore the patterns outlined above, I used a logistic regression analysis to determine if the two PCs (or an interaction between them) serve as predictors of early adopter status. As illustrated in Table 8.5, only PC1 serves as a statistically significant predictor of early adopter status in this case study, with PC2 and an interaction between PC1 and PC2 being shown not to be significant predictors. A Tjur's R2 test shows that the logistic regression model is a very weak fit at predicting early adopter status, with an R2 score of just 0.08.
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Input (early adopter) 0.055 Total N 2385
Deviance residuals: Min 1Q Median 3Q Max -2.8861 -0.2997 -0.2757 -0.2537 2.6822
Coefficients: estimate standard z value p value error (Intercept) -3.075e+00 1.035e-01 -29.711 p < 0.0001 PC1 (commenting 1.498e-02 1.422e-03 10.535 p < 0.0001 behaviour) PC2 -2.717e-02 1.751e-02 -1.551 p > 0.05 (inbound/outbound trajectory) PC1:PC2 (interaction) -3.721e-05 2.435e-04 -0.153 p > 0.05
Degrees of freedom: 2384 total; 2381 residual Null deviance: 1015 Residual deviance: 894.5 Akaike’s information 902.5 criteria (AIC) Table 8.5: Logistic regression model for the factors predicting early adopter status in the early adopter/non-adopter tea dataset.
Conclusion
In summary, in this chapter, I explored the extent to which the weak-tie theory of language change applies to an online CofP by looking at the status of the innovator and early adopters of tea in the Popheads community. The weak-tie theory of language change predicts that the innovators of linguistic forms will be peripheral members of their communities. On the contrary,
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formed', 'median score received', and 'moderator status') were not correlated with the role of being an early adopter. So, again, the hypothesis that 'members with high-status will be the early adopters of linguistic forms' may be too simplistic a way to conceptualise the complex relationship between status and early adoption. Finally, PCA and logistic regression were employed to determine the status markers that serve as statistically significant predictors of early adopter status. This research concluded, in a finding which is consistent with the previous chapters, that PC1 (commenting behaviour) was a statistically significant predictor of early adopter status. However, PC2 (which, this time, assigned more weight to the months active variable, with months remaining playing a much smaller role than seen previously) and the interaction between PC1 and PC2 were not found to be statistically significant predictors.
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9 Chapter 9: Discussion
The community of practice framework and the weak- tie theory of language change.
In Davies (2005), the author recommends that the principles of the weak-tie theory of language change (Milroy & Milroy 1985) should be incorporated into the CofP framework. Specifically, Davies (2005) proposes that peripheral members of a CofP will introduce innovations into a community and then the early adopters will be the full members who are central/core members of their community. Several sociolinguistic studies of offline CofPs reach conclusions which provide support for the relevance of the weak-tie theory to the CofP framework (Bucholtz 1999; Eckert 1988; Eckert 2000; Mendoza-Denton 2008; Moore 2010). The only research to date which has explored the applicability of the weak-tie theory to online CofPs, however, is Stewart et al. (2017), and, as explored in Section 2.6.3, this study has several potential methodological issues which mean that it may not be generalisable beyond its specific context. The lack of research on the subject of the weak-tie theory and online CofPs is problematic since studies of online social networks have suggested that the weak-tie theory may not be entirely relevant to virtual networks (Bergs 2006; Huffaker 2010; Kooti et al. 2012). Therefore, the extent to which the weak-tie theory of language change was applicable to online CofPs remained an open question that this research aimed to address through the exploration of the following three research questions:
RQ1.1 Does the weak-tie theory of language change's prediction about linguistic innovators hold in an online CofP?
▪ H1.1. Peripheral members will be the innovators of linguistic forms.
RQ1.2 Does the weak-tie theory of language change's prediction about early adopters hold in an online CofP?
▪ H1.2. Members with high-status will be the early adopters of linguistic forms.
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RQ1.3 Which status markers (if any) are statistically significant predictors of early adopter status?
▪ H1.3 All status markers will be statistically significant predictors of early adopter status.
RQ1.1 Does the weak-tie theory of language change's prediction about linguistic innovators hold in an online CofP
First, then, this research explored if innovations are introduced into a CofP by peripheral members. As discussed in Section 3.4.5, in offline studies, weak tie or peripheral members of a community are typically identified as those who fulfil few social roles or functions for other members of the community (Bax 2000; Milroy & Llamas 2013). These criteria are not straightforwardly adaptable to online communities. Therefore, I approached this study with a broader understanding of what it means to be a peripheral member of an online CofP. Specifically, to be a peripheral member is to post infrequently, to receive little attention on the posts that one does contribute, to be on an outbound trajectory, and to interact relatively infrequently with other members. In order to operationalise this definition of peripherality, I defined peripheral members as those who consistently score lower than the community median across four or more markers of status in the community. Thus, if the weak-tie theory of language change's prediction about linguistic innovators held in the Popheads online CofP, I would have expected the successful innovators of the four forms of interest to score lower than the community median on at least four of the eight quantitative markers studied. In contrast, three of the four innovators (
Form delete it fat buy x on iTunes wig tea Author
A notable exception to the finding that innovators are not peripheral members, however, is
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Overall, however, it would appear that the weak-tie theory of language change's prediction about linguistic innovators does not always hold in an online CofP. The hypothesis predicted that peripheral members would be the innovators of linguistic forms, but, on the contrary, three of the four innovators studied were demonstrably not peripheral members and instead scored highly on multiple markers of status in the community. Although this conclusion is unprecedented in the CofP literature, the findings are consistent with Bergs' (2006) theoretical predictions about innovators in online contexts. Indeed, he hypothesised that, in online social networks, "innovations now come from within, from the central network members, not from bridges or marginal positions" (Bergs 2006: 13). His argument was based, in part, on the different perceptions of offline and online linguistic creativity. Indeed, the Milroys argued that more central figures in offline social networks tend not to be innovators because it is too socially "risky" for them to introduce "potentially deviant" innovations into their network, presumably because of the possibility of rejection (Milroy & Milroy 1985: 368). However, while linguistic innovation seemingly poses too much of a social threat in offline communities, linguistic creativity is highly valued in many online contexts (Danet 2001: 2; Gillen 2018; Lazaraton 2014; North 2007; Stewart et al. 2017). Therefore, it may be perceived as less risky for central figures to behave as innovators in these virtual environments. Moreover, it is generally accepted that many individuals in online spaces have fewer inhibitions about behaviours perceived as risky in offline settings (Berdychevsky & Nimrod 2015; Carter 2019; Lemke & Weber 2017), a phenomenon which is known as the 'online disinhibition effect' (Suler 2004; Suler 2005). Overall, then, the theory that linguistic innovation in online communities does not carry the social risks associated with innovation in offline communities accounts for the finding that the majority of the innovators in the online CofP studied are not the peripherally connected members predicted in the CofP literature. Another factor to consider, however, is that a study of this kind, which uses an almost complete archive of all utterances from the community of interest, is unprecedented in offline sociolinguistic studies. Indeed, this research has been able to identify the very first instance in which each innovative form of interest was used in the Popheads community and thus identify the innovator. It would be almost impossible to replicate this level of completeness in the study of an offline community. Thus, it is worth considering if the real innovators in studies of offline communities may not have been discovered as a result of the necessary incompleteness of offline datasets and, in reality, may be less peripheral to the community than currently acknowledged. 227
One point to consider is that the term 'innovator', as used in this research, may be slightly problematic for a few reasons. Firstly, all of the expressions studied predate the Popheads community. Tea was in usage as early as the 1980s among the LGBT+ African American community (Hawkeswood & Costley 2003: 210) and folk etymologies date wig to approximately the same period (Gehring 2018). The 'true' innovator of delete it fat was Madison, the Demi Lovato fan who invented the hoax story and penned the fake threatening DM that first used the phrase. The innovator of buy x on iTunes is unknown, but the expression certainly predates the Popheads community. Therefore, none of the innovators discussed here actually invented the expressions attributed to them in this research. This is not problematic in and of itself, as there is a precedent in the sociolinguistic research for defining innovators not as the first person ever to use a variant, but rather the first person to use it in a given community (Labov 2001: 362; Milroy & Milroy 1985: 347). Where it does become potentially problematic, however, is when one considers that the innovators identified here may not have initiated the lexical diffusion processes in the Popheads community. More specifically, there is no way to determine if the first early adopter of a form read the post from the person deemed the successful innovator which 'introduced' the form into the community. It could be the case that the first early adopter had observed the form in use elsewhere (as all four forms are in use across social media sites such as Twitter, for instance) and that is what sparked them to use the word in the community, as opposed to being in any way influenced by the 'innovator's' usage. However, I have tried to control for this by evoking the concept of the 'unsuccessful innovator' to specify that if there is a notable gap between the innovation and early adoption, then we may be looking at an example of an unsuccessful innovator who had little to do with the diffusion process. Indeed, all individuals identified as successful innovators in this research saw their innovation taken up by an early adopter within twelve days of their first usage. Although the idea of the unsuccessful innovator (Bergs 2013; Bucholtz 1999) was evoked to control for a potential methodological limitation of this research, the study of the two unsuccessful innovators seen in this research was an interesting pursuit that raised questions which could be explored further in future research.
antagonistic behaviour and the initial failure of the innovation. Just as Bergs (2013) hypothesises that the orthographic innovation of the twelfth-century scribe may have failed because of the controversial personality of the innovator, the initial introduction of delete it fat into the Popheads community may have failed because of the problematic behaviour of
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RQ1.2 Does the weak-tie theory of language change's prediction about early adopters hold in an online CofP?
The weak-tie theory of language change holds that early adopters of innovations are central individuals/leaders in their network. This research aimed to explore if this finding could be replicated in an online CofP. I equated the classic concept of 'centrality' or 'leadership' with scores higher than the community median across multiple status markers in the Popheads community. Therefore, I analysed what percentage of early adopters fell above, below, or in line with the community medians across the status markers. This was a rather crude but effective way of achieving an overall picture of the status of the early adopters, especially as it was complemented by the more fine-grained statistical analysis that informs RQ1.3. Overall, the findings for this analysis were remarkably consistent across the four case studies. Specifically, there were four status markers on which over 55% of the early adopters consistently scored higher than the community median: 'months remaining' (60.9% - 71.4% scored higher than the community median for this variable), 'comments contributed' (79.7% - 96.7%), 'submissions contributed' (57.8% - 86.7%), and 'replies received' (59.4% - 77.1%). In general, then, the early adopters tended to be prolific contributors of both submissions and comments, who received a higher than expected number of replies to their posts and were on inbound trajectories in the community. On the other hand, there were a number of status marker variables that most early adopters did not score highly on. These were 'months active' (33.3% - 35.9% scored higher than the community median for this measure), 'one-link ties formed' (34.4% - 52.7%), 'ten- link ties formed' (40% - 51.7%), and 'median score received' (42.9% - 51.7%). These variables do not appear to be linked to early adopter status. Some of these findings were surprising in light of the existing literature. For instance, in Labov's (2001: 350-351) study of leaders of language change in Philadelphia, he concluded that one of the main leaders, Celeste, was defined by her centrality in her neighbourhood and her connections to a large number of other members of her network. Therefore, it was surprising that there was not a clear trend towards early adopters having a higher than expected number of one-link ties (a measure of the size of a member's social circle) in this study. In terms of the only non-quantitative variable studied, moderator status, there did not appear to be a strong relationship between membership of the Popheads moderation team and early adoption. The number of early adopters that were moderators ranged from zero (in the wig case study) to seven (in the tea case study). However, even in the latter instance, the
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moderators who were early adopters represented less than one-third of the moderating team. Therefore, moderator status does not seem to be a variable which correlates positively with early adopter status. Although there is a growing trend for research to consider the labour of volunteer content moderators (Cai & Wohn 2019b; Seering et al. 2019), there has been little work exploring the social behaviour of these users in online communities. However, it is possible to hypothesise that – all else being equal – moderators may behave more conservatively than regular members precisely because of the responsibilities associated with their moderator status. Therefore, it is perhaps not surprising that most moderators tend towards linguistic conservatism and do not serve as early adopters. Given that early adopters generally score higher than the community median on four variables associated with status in the community, one could tentatively argue that the hypothesis that high-status members will be the early adopters of linguistic forms holds in the Popheads online CofP. However, an important point to reiterate is that while the majority of early adopters do score higher than the community median on the four variables, a minority do not. Even when looking at the variable which seems to have the strongest relationship with early adopter status, 'comments contributed', in all case studies there were still adopters (specifically between 3.3% and 20.3% of the samples) who fell below the community median. One could argue that, in the vast majority of sociolinguistic studies, there will always be individuals who deviate from the expected trends. And, indeed, this argument does have merit. On the other hand, the exceptions to the rule make it difficult to form conclusions or unconditionally support hypotheses that verge towards broad generalisations, such as the one explored in this section. Perhaps a more accurate wording than "members with high status will be the early adopters of linguistic forms", would be "members with high status tend to be the early adopters of linguistic forms". However, even that statement is too simplistic as there were five status markers on which the majority of early adopters did not score highly ('months active', 'one-link ties formed', 'ten-link ties formed', 'median score received', and 'moderator status'). These findings suggest that not all of the status markers are created equal, and some are more associated with specific acts of influence than others or may be poor indicators of status in some contexts. In other words, the classical view of status as monodimensional is problematised by the findings here. To speak of a member as being 'high-status' is, ultimately, a non-specific term which fails to acknowledge the apparently complex and multidimensional nature of status in the community. 231
Perhaps a more accurate conclusion to draw then would be that members who are early adopters tend to be prolific contributors, whose posts are successful at generating discussion, and who are on inbound trajectories in the community. Future research should consider if these meaningful status markers correlate with specific personality traits or types. For instance, someone who is successful at creating posts which generate replies may be particularly charismatic and extroverted, and it may thus be underlying personality traits which are contributing factors in predicting early adopter status. Although this theory is highly speculative at this stage, a research design inspired by third- wave sociolinguistics methodology could interrogate this hypothesis further.
RQ1.3 Which status markers are statistically significant predictors of early adopter status?
In RQ1.2, I explored relatively simply quantitative measures, in order to determine if early adopters scored highly across multiple markers of status in the Popheads community. With RQ1.3, I was interested in determining if any status markers served as statistically significant predictors of early adopter status. Based on the existing literature, which equates high-status members with the role of early adopter, I hypothesised that all status markers may be significant predictors of early adoption. Because of both the large number of status markers analysed in the data and the emerging theme that power may be more complex and multidimensional than typically conceptualised, I opted to use PCA to explore this research question. PCA transforms the numerous variables associated with status in the inputted datasets into a smaller number of variables which, nevertheless, retain most of the information in the original dataset and also allow for a multidimensional overview of status. Each of the four datasets explored contained information about 1) the status markers for the early adopters of the forms and 2) the full members who were active during the early adoption period, but who did not adopt the innovation. The decision was made to focus on the two PC variables which explained the largest amount of variance in the datasets and any other PCs which explained 5% or more of the variance. However, across all of the case studies, outside of the first two PCs, no individual PC accounted for more than 5% of the variance, meaning that no additional PCs were examined in any of the case studies.
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The findings of the PCA and subsequent logistic regressions are summarised in Table 9.1 below:
Form delete it fat buy x on iTunes wig tea PC1 - Percentage of variance explained 93.38% 92.06% 93.78% 96.1% PC1 - Primary contributing variable comments comments comments comments and loading value contributed (1) contributed (1) contributed (1) contributed (1) PC1 - Statistical p < 0.0001 p < 0.0001 p < 0.0001 p < 0.0001 significance PC2 - Percentage of variance explained 4.24% 5.26% 3.17% 1.96% months active PC2 - Primary months months months (0.93) & contributing remaining (1) & remaining (0.99) remaining (0.92) months variable(s) and months active & months active & months active remaining loading value(s) (0.09) (0.14) (0.4) (0.36) PC2 - Statistical p < 0.01 p < 0.001 p < 0.01 p > 0.05 significance PC1:PC2 interaction statistical p < 0.0001 p > 0.05 p < 0.05 p > 0.05 significance Table 9.2: Summary of PCA and logistic regression results.
It was consistently the case that PC1, which the loadings showed was primarily a measure of 'comments contributed' and which was thus referred to as 'commenting behaviour', accounted for the overwhelming majority of the variance in the datasets (between 92.1% and 96.1%). This means that most of the information in the datasets can be summarised by looking solely at PC1 and that this is a disproportionately important variable when considering status in the inputted datasets Examinations of the relationship between PC1 and early adopter status showed that early adopters generally posted more comments than their non-adopting counterparts. This fits with the findings presented in the previous section regarding the large percentages of early adopters (79.7% - 96.7%) who contributed more comments than the community median. The logistic regressions showed that PC1 served as a statistically significant predictor of early adopter status across all of the case studies (p < 0.0001). The second variable of interest was PC2. This variable accounted for between 1.96% and 5.26% of the variance across the datasets, and the loadings for delete it fat, buy x on iTunes, and wig showed that this was primarily a measure of 'months remaining' and, to a much lesser extent, 'months active'. In these three case studies, PC2 was referred to as
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'inbound/outbound trajectory' An examination of the PCA results showed that early adopters were generally more likely to score higher on PC2 than non-adopters, indicating that the majority of this group were on inbound trajectories in the community. Moreover, PC2 was consistently shown to be a statistically significant predictor of early adopter status in the delete it fat (p < 0.01), buy x on iTunes (p < 0.001), and wig (p < 0.01) case studies. In the tea case study, however, the loadings showed a reversal of the pattern described above: it was 'months active' that constituted the greatest contribution to PC2, whereas 'months remaining' was a minor factor. In that instance, PC2 was thus labelled 'time active in the community'. However, PC2 was subsequently found not to be a statistically significant predictor of early adopter status in the tea case study. Notably, it was also in the tea dataset that PC2 accounted for the lowest proportion of the variance seen in this research (just 1.96%). There is no obvious reason why the tea dataset differed so markedly from the other case studies in relation to PC2. It may be the case that there was something inherent in tea, the contexts in which it was used, its place in the community's shared linguistic repertoire, or another unaccounted factor which led to the status profile of early adopters differing for this innovative form. A closer qualitative analysis of tea, in a future study, may help explain the findings described here. The possibility of interactions occurring between PC1 and PC2 was also considered in light of the emerging finding that the relationship between early adoption and status does not seem to be a simple phenomenon in an online CofP. Findings in Table 9.1 above show that, in the delete it fat and wig case studies, there is a statistically significant interaction (at p < 0.0001 and p < 0.05 respectively) between PC1 and PC2 when it comes to predicting early adopter status. Specifically, scoring highly on both PC1 and PC2 (and thus being a prolific commenter on an inbound trajectory) is a significant predictor of early adopter status. The buy x on iTunes and tea case studies show no comparable statistically significant relationship between the two PCs (p > 0.5 in both instances). Nevertheless, one thing that must be considered when interpreting the logistic regression models is that all the models were found to have very poor levels of predictability using Tjur's R2 coefficient of discrimination. The Tjur's R2 test returns coefficient values relating to the level of predictability provided by each logistic regression model: a perfect model has a score of 1, a model which offers no predictability has a score of 0. Across the four case studies, the Tjur's R2 coefficients were extremely low, ranging from 0.06 to 0.16. These results do not necessarily problematise the findings relating to the significant relationships between the status variables and early adoption: the relationships are still 234
significant. However, what this does suggest is that there are other factors at play which affect early adopter status that this study did not explore. Given the number of variables significant to first and third-wave sociolinguistic research that this study was, unfortunately, not able to account for (see Section 3.5), this finding is perhaps unsurprising. To summarise, the starting hypothesis that all status markers would be statistically significant predictors of early adopter status was too simplistic. The relationship between status and early adoption can be mapped, but it is a complex and multidimensional relationship which resists vast generalisations and differs slightly in its manifestations across the four case studies. H1.3 must therefore be rejected as not all markers were statistically significant. Nevertheless, specific individual status markers have been shown to be statistically significant predictors of early adopter status. Specifically, PCA transformed the numerous status markers in the original dataset into two new variables that explained the vast majority of the information in the dataset. The PCA and logistic regression analysis showed that PC1 (commenting behaviour) is consistently a statistically significant predictor of early adaptor status. Additionally, PC2 (inbound/outbound trajectory) was a significant factor in three of the four case studies, while an interaction between PC1 and PC2 was found to be a statistically significant predictor of early adopter status in two of the four case studies, indicating a strong multidimensional component to the relationship between status and early adoption. Thus, instead of using vague terms such as 'high-status' members to describe early adopters, this research advocates for the use of terms which more specifically describe the behaviours and status markers which are statistically correlated with early adoption (that is, relatively prolific commenting and, in most cases, being on an inbound trajectory).
Power, status, and the control of linguistic resources in an online Community of Practice.
A key aim of this research was to contribute to the ongoing debate about the relationship between power and status in CofPs. Specifically, this research explored issues relating to status, hierarchy, and power in the online CofP Popheads by exploring the advocation, implementation, and effectiveness of endogenous LCM policies. This approach was chosen, in part, as a response to the lack of existing work which specifically explores the language of CofPs, my aim being to further the understanding of the power dynamics which shape and control shared linguistic repertoires. The second motivation
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for this approach was to contribute to the study of LCM in online CofPs. Exogenous LCM has been studied widely (Chancellor et al. 2016; Chen, Zhang & Wilson 2013; Stewart et al. 2017; Wozniak 2015), but this study is the first to consider the impact and effects of endogenous content moderation on a community. Although one could argue that focusing solely on endogenous LCM policies is somewhat of a niche way of approaching the study of status, hierarchy, and power in an online CofP, it is nevertheless a worthwhile avenue of research, which allows for a focused and systematic exploration of a complex and broad area of study. The hypotheses explored in this research were primarily derived from the CofP literature and reflect the variety of conceptualisations of the relationship between status, hierarchy, and power proposed by scholars in this field:
▪ H2.1 CofPs are composed of horizontal power structures (Kerno 2008; Wenger 2010). ▪ H2.2 CofPs are composed of vertical hierarchical structures, and those at the top control and influence the community and its resources (Davies 2005; Silva, Goel & Mousavidin 2009). ▪ H2.3 CofPs may have top-down hierarchical structures, but all legitimate members can potentially control/influence the community and its resources (Moore 2006). ▪ H2.4 The conceptualisations of the relationship between power and hierarchy in H2.1 – H2.3 are too simplistic.
This discussion will now consider each of the hypotheses in light of the findings outlined in Chapters 5-8, before concluding by answering the research question 'who has the power to control or influence linguistic resources in the Popheads CofP?'.
H2.1 CofPs are composed of horizontal power structures (Kerno 2008; Wenger 2010). Of all the hypotheses explored in this work, H2.1 is the one that is least compatible with the findings of this research. The very existence of moderators – a group of undemocratically selected users who can create rules relating to language use, delete other members' posts, and even ban others from the community – is incompatible with the idea of a horizontal power structure.
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The idea of CofPs being composed of horizontal power structures presupposes that no single person or sub-group will have power over anybody else in the community. However, this view seems not only incompatible with the findings of this research, but also the behaviour of most social communities. Indeed, Turner (2005: 18) writes that power is fundamental to social cohesion and that "for a group to pursue its collective will there must be a power structure through which group identity and goals are realized". This hypothesis is primarily propagated in the workplace/organisational literature and, in that context, is contrasted with the traditional vertical hierarchical structures associated with organisational domains (Kerno 2008; Wenger 2010). Therefore, it is perhaps the case that this view is specific to the way in which power works in certain organisations that have chosen to implement the horizontal model (as opposed to other traditional models of power in the workplace). The extent to which this hypothesis holds in more social or interest-based CofPs is highly dubious since the vast majority of studies of CofPs in these contexts, including this current work, have identified individual members or sub-groups who can influence and/or control other members (e.g. Kendall 2008; Moore 2006; Paechter 2006; Silva, Goel & Mousavidin 2009; Stommel & Koole 2010).
H2.2 CofPs are composed of vertical hierarchical structures, and those at the top control and influence the community and its resources (Davies 2005; Silva, Goel & Mousavidin 2009). The second hypothesis was primarily derived from the work of Davies (2005), who argues that a vertical hierarchical structure is necessary to manage access to and participation within a CofP. In this view, a select number of members have control over the community and its resources, they can "wield" power over those who are lower down in the hierarchy, and other members and outsiders recognise their power. There are clear similarities between this conceptualisation of the unparalleled power of members at the top of the hierarchy and the role of the moderators in the Popheads community. Indeed, the moderators are the only members in the CofP who have official power, and the findings throughout have shown that they can control the linguistic resources in the Popheads CofP. Indeed, in Chapters 5-6, I discussed how the moderators formulated and implemented an LCM policy that only they could control. There were alternative LCM policies proposed by members that could have been promoted or implemented by the moderators, including self-moderation or more reliance on the democratic upvote/downvote system for regulating content. Instead, however, the moderators opted for the top-down LCM policy. Under this 237
policy, they decided which words or phrases were allowed to be used in the community, chastised users for violating the LCM policy, and removed other members' posts. Their policy also permitted them to ban members for violating the rules. Although there is no evidence that any member was ever banned from the community for flouting the LCM policy, there is, nevertheless, evidence that the possibility of being banned for LCM violation served as a source of anxiety for some members. To summarise, one way in which the moderators controlled the linguistic resources of the CofP was by introducing an LCM policy that was fully orientated around the exclusive powers of the moderators, giving non- moderating members little-to-no control over its implementation or enforcement. Moreover, in the announcement of the January 2017 LCM policy (in which delete it fat and buy x on iTunes were banned), the moderators' tone was described by one member as 'harsh'. The moderators attempted to discursively redefine what it means to be a member of the Popheads community and wrote that members who wished to continue using the terms covered under the policy were no longer welcome. In other words, then, the moderators did not attempt to mitigate the force or impact of the LCM policy on the community. They announced the policy in an authoritarian way that emphasised their power and left no room for negotiation or debate. The tone in the announcement for the banning of wig in May 2018, however, was markedly less severe. Indeed, by that point in time, LCM had become an established part of the community's repertoire and did not require a top-down show of power and authority to embed it in the community. The LCM policy gave the moderators the power to punish other members for violating the policy and using banned terms. There was evidence that moderators had removed posts containing banned forms; however, the most notable punishment evident in the Popheads corpus is public chastisement. There are multiple instances demonstrated throughout the first two case studies in which moderators reinforce their control over the community's lexicon by publicly drawing attention to members who have violated the LCM policy and chastising them in front of their peers. Nevertheless, the moderator's unique position in the community also gave them the freedom to violate their own LCM policies. Members of the moderating team were responsible for a remarkable 11% of all LCM violations recorded in the corpus. One moderator explicitly drew on his status in the community to legitimise his use of a banned form, another violated the LCM policy while chastising a non-moderator for violating a community rule, and a rate host expressed anxiety that a crucial post in the rate reveal might be deleted because a moderator had used a banned form in his review. These acts, arguably, 238
can be categorised as low-level abuses of power: their moderator status in the community allows these members to behave in a way that would be deemed unacceptable from a non- moderating member. Therefore, the findings of this research provide some support for H2.2. Those at the top of the hierarchy of the community (or, more accurately, one of the hierarchies of the community) do draw on their power to implement, enforce, and, in some instances, violate, LCM policies which allow them to control aspects of the community's lexicon. There is a clear link between status (and specifically moderator status), hierarchy, and power: the power to implement and enforce LCM is dependent entirely on a member's (moderator) status. However, there is also a great deal of evidence presented in Chapters 5-8 which problematises H2.2. Firstly, the introduction of LCM was seemingly influenced by complaints from non-moderating members who felt that their experience in the community was negatively impacted by the overuse of certain forms. Delete it fat, specifically, was a particular target of these complaints. Although members did not specify that they would like a top-down LCM system to be introduced, several were implicitly advocating for some form of LCM policy to lower the frequency of these forms and reverse the perceived detrimental effects of their ubiquity on the community. Furthermore, several non-moderating members also celebrated and welcomed the LCM polices after their announcement. In other words, the decision to introduce LCM was influenced by members who were excluded from the moderator hierarchy, and it would be unreasonable and unfair to argue that the moderators unilaterally forced LCM upon the community. Non-moderating members drew attention to the need for LCM in the CofP and the moderators, albeit strongly and in a top-down fashion, were responding to their call. Secondly, it was demonstrated in the wig case study that, once LCM was an established part of the CofP's repertoire, non-moderating members explicitly drew on the precedent of existing LCM policies to try and influence the moderators to add new forms to the list of banned terms. The moderators' unique power to ban words had become a tool that members who were excluded from that power could utilise their status to petition for. Status is not as simple as existing on one top-down hierarchy: there are multiple factors which can give a user status in the community and thus, seemingly, the ability to influence LCM policies. Thirdly, if the moderators did have full control over the linguistic resources of the Popheads community, the three banned forms would have become obsolete in the community. However, this was clearly not the case. All three banned forms remained in 239
usage in the community after the point of the ban and until the end of the data collection period. Collectively, the three LCM policies explored in this study were violated over 500 times by over 340 different members, who refused to let the moderators dictate the shared repertoire of the community and instead took back control of their lexicon. Fourthly, the LCM rules were not met passively by non-moderating members. For instance, Chapters 5 and 6 described how members complained about the LCM policies and accused the moderators of being too 'heavy-handed' in their decision to introduce a top-down policy. Meanwhile, another member confronted a moderator and accused him of not understanding the LCM policy after he had publicly chastised a flouter. Furthermore, in Chapter 5, the findings showed that some members turned violations of the LCM policy into a ludic game, thinking of new and creative ways of articulating banned LCM forms, including the use of synonym variants, irrealis hypothetical constructions, and strikethrough effect. Part of the appeal of these linguistically creative forms was undoubtedly the power that they give non-moderating users to undermine and interfere with the LCM policy: members showed explicit awareness that their creative violations were rebellious, and they characterised their behaviour as a subversion of the moderators' power. Members also expressed delight at frustrating the moderators and driving them 'insane' through their linguistic creativity. The moderators may theoretically control the linguistic resources of the community, but some members are not respectful of that power and make deliberate, and arguably successful, attempts to subvert their authority and regain control of the lexicon. Fifthly, the moderators' violation of their own rules was not allowed to pass without comment from non-moderating members. For instance, in response to
the community for the moderators to review. Just because the moderators have the power to control the linguistic resources of the community, it does not mean that they will always have the time or the inclination to screen all comments to ensure compliance with the LCM policies. More simply, just because the moderators theoretically can control the linguistic resources of the community, does not mean that they will do so in practice. Therefore, this research concludes that the hypothesis that 'CofPs are composed of vertical hierarchical structures, and those at the top control and influence the community and its resources' cannot be fully supported by the evidence presented in Chapters 4-6. The hypothesis is too simplistic – both in its conceptualisation of hierarchy as a unidimensional concept and in its envisioning of one sub-group of members as having totalitarian control, while the rest of the community are characterised as passive and agentless objects of their will.
H2.3 CofPs may have top-down hierarchical structures, but all legitimate members can potentially control/influence the community and its resources (Moore 2006). As recapped above, this research has shown that non-moderating members were highly influential in advocating for LCM and were also able to take back control of their lexicon by violating and subverting LCM rules. So, on a superficial level, H2.3 can be supported, since members who are not at the top of the moderator hierarchy can demonstrably influence and control the community's linguistic resources. However, supporting H2.3 would be problematic for two key reasons. Firstly, this hypothesis is still working within the unidimensional view of hierarchy and status criticised above, which problematically and inaccurately assumes that there is only one hierarchy (that is, the moderator hierarchy) in the community. Secondly, H2.3 predicts that anyone can control the linguistic resources of the community, but what I have found here is that the vast majority of the Popheads members who seem to be able to influence or control the linguistic resources of the community score highly across multiple markers of status. Therefore, not everyone who is a member of the community appears to have an equal chance to control or influence the linguistic resources. Members who have moderator status can control the usage of forms by setting and enforcing LCM policies (although their power is not always effective or exercised). Meanwhile, members who have markers of unofficial status have the ability to influence and assert control over linguistic resources by, for instance, advocating for LCM or violating LCM policies. However, to say that any legitimate member can control or influence linguistic 241
resources in the Popheads community is an oversimplification of the relationship between power, hierarchy, and status in the community studied.
H2.4 The conceptualisations of the relationship between power and hierarchy in H2.1 – H2.3 are too simplistic. Instead, I argue that the findings of this research most strongly support H2.4. A major issue with the way power is treated in H2.2 and H2.3 (and thus, by extension, a great deal of the CofP literature) is that hierarchy and status are assumed to be monodimensional. Instead, I argue that there are multiple hierarchies at work in a CofP and scoring highly on certain status hierarchies may correlate with the power to control or influence certain aspects of the linguistic resources of the community. For instance, having moderator status (one hierarchy) will give members the power to implement LCM policies. However, scoring highly on other hierarchies (such as 'comments contributed') may correlate with alternative forms of linguistic influence and control, such as advocating for or violating LCM policies. The relationship between power, status, and hierarchy is not simple and straightforward. The multidimensional nature of status – which resists the idea of being captured in a single measure – means that the relationship cannot be simple. However, that does not mean that there is no relationship – there demonstrably is – or that the relationship cannot be captured and described using methods such as those demonstrated in this work. I argue that future studies of power in CofPs must be open to the idea that the dynamics of a community cannot be captured in a single hierarchy and there may well be multiple status factors which structure and define the hierarchies of the community. Of course, the status factors which correlate with power will likely differ markedly from community to community, and ethnographic work will be needed to understand which status factors are important. However, my hope is that this work may serve as a blueprint to inform the consideration of status in future CofP studies and especially those centred on online CofPs.
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10 Chapter 10: Conclusion
Introduction
This thesis concludes by exploring the significance of the findings presented here and the contributions they make to the linguistic discipline. Finally, I consider the limitations of my work and propose areas for future research.
Contributions
The research demonstrates that the first principle of the weak-tie theory of language change, which states the innovators of linguistic forms will be peripheral to the community, does not always hold in an online CofP. This finding is important in two ways. Firstly, it has implications for those interested in processes of language creativity in online environments, since it can serve as a starting point for identifying potentially innovative members of a community. Secondly, this finding potentially calls for a re-examining of how innovators are conceptualised not only in online communities but also in offline environments. Indeed, one of the key advantages of this work is that I have been able to study a near-complete archive of all interactions in a community for the first thirty-four months of its existence. I was, thus, able to trace the very first time innovative forms were used in the community and identify their innovators. It would be almost impossible to undertake such a procedure in an offline study. Thus it is worth considering if the real innovators in studies of offline communities may have been mislabelled or undiscovered as a result of the necessary incompleteness of offline datasets. Secondly, this research found that descriptors such as 'high-status' were vague and unsatisfying when describing the characteristics of early adopters in a CofP. There are multiple hierarchies at work in the community investigated: a hierarchy of comment contributors, of submission contributors, of people who receive the most replies, and so on. What is important when predicting early adopter status is not where an individual member sits on a single hierarchy, or if they are a 'high-status' member of the community, but rather where they sit on multiple hierarchies and their position in the intersection of those hierarchies. Therefore, the second contribution that this research makes is the finding that
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identifying the hierarchical structures that underpin a community and then exploring early adopters' positions in those structures can lead to significantly more precise descriptions of the characteristics of early adopters. For instance, in this case, instead of concluding that most early adopters are high-status members of the community, it has been possible to reach the more precise and satisfying conclusion that early adopters are significantly more likely to be prolific commenters on an inbound trajectory in the community. Similarly, in this research, I developed a method, which was informed by an extensive literature review and ethnographic observations, for measuring status as a multidimensional concept. This method may or may not be directly generalisable beyond the Popheads community (or, more optimistically, Reddit), but it nevertheless provides a template which can be adapted, following ethnographic observation, to the nuances of online communities of interest to future researchers The fourth contribution that this research makes is to the conceptualisation of power, status, and hierarchy in linguistics. Primarily, this research was interested in clarifying the relationship within the CofP framework. However, the general conclusions reached regarding the multidimensional nature of status hierarchies and the complex interplay between status, hierarchy, and power may be informative for the linguistic study of power in social communities more broadly. A final contribution is to the study of endogenous LCM. This is the first study to explore LCM in an environment where the content moderation policies have been put in place by members of the community as opposed to outsiders. This is an interesting linguistic context, and the findings regarding how LCM policies are protested, subverted, and violated by members with high-status markers may be of interest to scholars interested in power and linguistic censorship.
Limitations and future research directions
Firstly, one of the critical limitations of this work is that the low Tjur's R2 scores on the logistic regression models when considering statistically significant predictors of early adopter status strongly suggest that variables are missing from this analysis which would contribute to the understanding of the hypotheses. Indeed, while this work extensively explores status variables, there are many factors which have previously been shown to be significant to language variation and change in sociolinguistics that are not considered. For
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instance, first-wave sociolinguistic variables, such as age, gender, and socio-economic status, were not explored at all because of the impracticality of gathering this information from thousands of members. Additionally, if time had permitted, it would have been worthwhile to undertake a third-wave sociolinguistics (Eckert 2012; Eckert 2018) informed qualitative exploration of the relationship between power, status, and the personas projected by members of the CofP. Future research could thus expand on the findings presented in this work by broadening the research design to explore social, stylistic, and identity variables which may serve as significant predictors when looking at innovation, adoption, and status in this CofP. On a similar note, this research was focused entirely on interactions that occurred in the public Popheads community. It is possible that further insights could have been gained if the research scope had been expanded to explore other online communities that a large number of Popheads members belong to (such as, for instance, r/popheadscirclejerk, the Popheads spin-off Reddit community for 'shitposts'). Similarly, when exploring status, only markers of status gained from participation within the Popheads community were considered. However, research has shown that a member's status within a CofP can be impacted considerably by recognition from outsiders or external communities (Kendall 2008: 500). For instance, if a respected member of another community whose userbase overlaps considerably with Popheads joins the community, they may bring a degree of status with them based on their contributions to the external group. Therefore, future research would likely benefit from considering the interactions and overlaps between the primary research community and other online networks. Thirdly, this research was conducted without contacting any of the members studied to discuss or confirm my interpretation of community practices and discourses. Although, as discussed by Carter (2004: 177), there are potential methodological issues in retrospectively asking participants to analyse their discursive intentions and responses, it would nevertheless have been an interesting pursuit to determine the extent to which my analysis conforms to members' own understanding of events. A particularly valuable avenue of research to explore would have been to interview the Popheads moderators about the LCM-related work that happens 'behind the scenes' of the community. This would be a worthwhile project to explore in future research in order to expand on and increase the reliability of the qualitative analysis presented in this work. Finally, the complex relationship between status, hierarchy, and power in a CofP is considered here only through the lens of LCM. This approach allowed for a focused and 245
systematic exploration of one facet of power. However, it nevertheless means that many other aspects of the manifestations of power in online CofPs (such as, for instance, managing and negotiating access to the community) can be explored in future studies to expand on the understanding of the relationship between status, hierarchy, and power in the CofP framework.
Concluding remarks
This thesis focused on the study of the innovation, diffusion, and LCM of four innovative linguistic forms in the Popheads CofP. The almost-complete longitudinal corpus of posts from the online CofP has allowed for an in-depth exploration of the role of innovators, early adopters, and the relationship between status, hierarchy, and power that is unprecedented in offline sociolinguistic studies. I hope that although the conclusions reached here are linked closely to the CofP framework, the methodology and findings will be of interest and significance to scholars in sociolinguistics and cognate fields of study more broadly. Turner (2005: 1) writes that "power is an inescapable feature of human social life and structure". This research demonstrates that future linguistic studies which aim to understand the functioning and dynamics of social communities should not assume that status and power will operate in a linear fashion but be open to the idea that these are complex and multidimensional concepts that need to be treated as such when creating research designs and interpreting findings.
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