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Exploring the Relationship Between Membership Turnover and Productivity in Online Communities

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Exploring the Relationship Between Membership Turnover and Productivity in Online Communities Proceedings of the Eighth International AAAI Conference on Weblogs and Social Media Exploring the Relationship between Membership Turnover and Productivity in Online Communities Xiangju Qin], Michael Salter-Townshend},Padraig´ Cunningham] ]School of Computer Science & Informatics, University College Dublin }Department of Statistics, University of Oxford [email protected], [email protected], [email protected] Abstract suggesting that Wikipedia experiences high level of mem- bership turnover. One of the more disruptive reforms associated with the modern Internet is the emergence of online commu- nities working together on knowledge artefacts such as Wikipedia and OpenStreetMap. Recently it has be- come clear that these initiatives are vulnerable because of problems with membership turnover. This study presents a longitudinal analysis of 891 WikiProjects where we model the impact of member turnover and social capital losses on project productivity. By exam- ining social capital losses we attempt to provide a more nuanced analysis of member turnover. In this context social capital is modelled from a social network per- spective where the loss of more central members has more impact. We find that only a small proportion of WikiProjects are in a relatively healthy state with low levels of membership turnover and social capital losses. The results show that the relationship between social capital losses and project performance is U-shaped, and that member withdrawal has significant negative effect Figure 1: Statistics of Yearly Active Editors in English on project outcomes. The results also support the medi- Wikipedia from 2001 to 2013. The data for 2013 was only ation of turnover rate and network density on the curvi- till August 5, 2013. linear relationship. In traditional organizations, the cost of leaving a job can Introduction be extremely high in terms of sacrificing material or psy- With the popularity of Web 2.0, recent years have witnessed chological benefits, such as giving up colleagues, interesting a growing population of online communities which rely on projects, corporate stock and pension benefits (Mitchell et al. contributions from online volunteers to build knowledge and 2001). By contrast, in online communities, without commit- software artifacts. Despite the success of a few communi- ting to any tasks, projects, or conversations, the barriers to ties, such as Linux, Apache, Wikipedia and OpenStreetMap, entry and exit are very low, each participant is free to join many of them fail to generate desired outcomes. Many of and leave (Ransbotham and Kane 2011). Joining an online these failures are due to the intrinsic characterstics of open group can be as easy as filling in a form or writing a pro- collaboration in online communities, namely, high levels of file (Dabbish et al. 2012), leaving an online group is even member withdrawal (Faraj, Jarvenpaa, and Majchrzak 2011; easier by stopping contributions or showing no activities in Ransbotham and Kane 2011). Even in successful online the community. For volunteers, leaving an online commu- communities, such as the English version of Wikipedia, high nity generally incurs little cost (except losing opportunity to churn in membership is still the norm, with 60% of regis- learn from peers). While for the online community, mem- tered users staying only a day (Panciera, Halfaker, and Ter- ber withdrawal can have a significant influence on its func- veen 2009; Dabbish et al. 2012). Figure 1 presents the statis- tionality: membership turnover may improve group perfor- tics of yearly active registered editors in English Wikipedia mance by bringing in novel skills and expertise, but it may from its inception. Figure 1 shows that each year the num- also threaten the cognitive structures and processes that are ber of new editors dominates the amount of active editors, so useful for expertise coordination (Lewis, Belliveau, and Herndon 2007; Faraj, Jarvenpaa, and Majchrzak 2011), and Copyright c 2014, Association for the Advancement of Artificial inevitably disrupt routines and established social ties and Intelligence (www.aaai.org). All rights reserved. further reduce its social capital (Shaw et al. 2005). 406 High membership turnover in online communities has at- those who remain behind enjoy better working conditions tracted much attention from researchers to study the influ- and performance (Krackhardt and Porter 1985). A third per- ence of turnover on community health. The most dominant spective suggests that moderate levels of turnover lead to view suggests that membership turnover is disadvantageous the best organizational performance (Abelson and Baysinger to effective collaboration, and the ability to engage and re- 1984) in terms of creating opportunities for organizations tain members represents a key aspect of success (Arguello et to access new skills and knowledge through the influx of al. 2006). Those who leave the community, take with them new employees (Madsen, Mosakowski, and Zaheer 2003). not only unique knowledge and insight, but also the experi- In their empirical study on 38 locations of a restaurant chain, ence and social relationships they have gained and estab- Shaw et al. found that employee turnover rate moderates lished through participation. On the other hand, some re- the curvilinear relationship between social capital losses and search suggests that the unique capabilities of Web 2.0 tech- performance. Despite the fact that online communities (e.g., niques could help mitigate the negative effects of turnover. Wikipedia) generally experience considerable membership For example, Web 2.0 platforms are typically equipped turnover, the effects of turnover on collaborative outcomes with functions to preserve all previous contributions by past in these communities are not well understood. members in an organized and searchable manner, so as Because online communities rely on the contributions of to facilitate the utilization of past contributions for future volunteers to survive and succeed, member turnover can community members as needed (Kane and Fichman 2009; have significant effects on collaborative activities in terms Wagner and Majchrzak 2006). While these studies shed light of resource availability and the health of a community. on the relationship between turnover and performance in the Faraj, Jarvenpaa, and Majchrzak suggested that the fluid- online scenario, a major limitation is that they fail to con- ity of members can bring opportunities for knowledge col- sider social capital loss through member turnover and its im- laboration when managed appropriately. By experiments on pact on the functionality of communities. 2,065 featured articles from Wikipedia, Ransbotham and Despite its success as a means for knowledge sharing and Kane found a curvilinear relationship between the turnover collaboration, little is known about the mechanism behind of Wikipedia editors and the quality of an article. Specifi- Web 2.0 platforms from the perspective of social network cally, they discovered that a Wikipedia article edited by ex- analysis. The social network approach provides a unique perienced editors is more likely to be of higher quality up perspective to study the evolution of online communities to an optimal level of experience, after which the average over time, and to study the resilience of social networks experience of editors decreases the quality of the article (by against node removal (i.e., member drop-out) in these plat- demoting it from FA status to lower quality status). Wang forms. In this study, we take a social network approach to in- and Lantzy provided a framework to systematically examine vestigate the relationship between member turnover, social the relationship between member turnover and the health of capital losses and group performance in WikiProjects. We a community, where community health is measured as the are interested in the following questions: Does the drop-out content volume, traffic, responsiveness, interactivity of the of members in different network positions have the same ef- community. However, the authors haven’t provided empir- fect on group performance? How does social capital loss due ical results to evaluate their hypothesis. Zanetti et al. stud- to departing members influence group performance? Is there ied the evolution of social structual in open source software consistency across the evolution of online groups? Overall, communities along multiple dimensions, such as the cohe- the eventual goal of this study is the provision of multi- siveness of the communities, the distribution of responsibil- dimensional indicators related to the health and performance ities and the resilience against membership turnover in the of online communities, which provides insight into the man- community. However, this study is limited in that it did not agement and evaluation of these communities. take into account community performance indicators. Dif- The rest of this paper is organized as follows. The next ferent from other studies, Kivran-Swaine, Govindan, and section provides a brief review of related work. In Section Naaman explored the breaking of ties using social network 3, we explain network measures and project characteristics theories and found that network structure can significantly related variables, and develop hypotheses. Next, we discuss explain the breaking and persistence of ties in online ser- data collection and model specification. Section 5 presents vices like Twitter. the results, followed by discussion and
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