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Conformity Behavior in Music Playlist Creation in a Group Conformity Behavior in Group Playlist Creation Christine Bauer Bruce Ferwerda Abstract Johannes Kepler University Linz Jönköping University A strong research record on conformity has evidenced that Institute of Computational Department of Computer individuals tend to conform with a group’s majority opin- Perception & LIT AI Lab Science and Informatics ion. In contrast to existing literature that investigates con- Linz, Austria Jönköping, Sweden formity to a majority group opinion against an objectively [email protected] [email protected] correct answer, the originality of our study lies in that we in- vestigate conformity in a subjective context. The emphasis of our analysis lies on the concept of “switching direction” in favor or against an item. We present first results from an online experiment where groups of five had to create a music playlist. A song was added to the playlist with an unanimous positive decision only. After seeing the other group members’ ratings, participants had the opportunity to revise their own response. Our results suggest different conformity behaviors for originally favored compared to dis- liked songs. For favored songs, one negative judgement by another group member was sufficient to induce partici- pants to downvote the song. For originally disliked songs, in contrast, a majority of positive judgements was needed to induce participants to switch their vote. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation Author Keywords on the first page. Copyrights for third-party components of this work must be honored. Conformity behavior; social influence; music playlist cre- For all other uses, contact the owner/author(s). CHI ’20 Extended Abstracts, April 25–30, 2020, Honolulu, HI, USA. ation; group music playlists; group recommendation. © 2020 Copyright is held by the author/owner(s). ACM ISBN 978-1-4503-6819-3/20/04. http://dx.doi.org/10.1145/3334480.3382942 CCS Concepts how do people conform in a group-decision setting of pref- •Human-centered computing ! User studies; Empiri- erences and taste? cal studies in HCI; •Applied computing ! Psychology; •Information systems ! Recommender systems; This paper is structured as follows: First, we present the conceptual basis and discuss related work. Then, we detail Introduction the study design of our online experiment. After reporting Social influence and conformity have been studied in face- the results, we discuss the findings and implications, and to-face situations for a long time [32]. While social influence point to future research. has been studied in online settings as well [40, 39], confor- mity has received far less attention [32]. Most online con- Conceptual Basis and Related Work formity research focuses on conformity to group norms in Social influence refers to the change in an individual’s thoughts, online communities (e.g., [35, 28]) or on conformity in ex- feelings, attitudes, or behavior resulting from the interac- pression in online reviews (e.g., [16]). Yet, there are other tion with another individual or a group [37]. Responses forms of online group scenarios that deserve attention. Al- to social influence may take forms of conformity or non- gorithmic decision-making for groups, for instance, is an conformity [27]. In this work, we focus on conformity which increasingly important topic (e.g., [21, 34]. is a concept from social psychology and was coined by Asch [1,2,3]. It refers to the phenomenon that individuals A special form of algorithmic decision-making for groups tend to forgo their personal strategy (e.g., opinion, prefer- are so-called group recommender systems [26] that com- ence) and adopt the conflicting majority variant [36]. pute the most relevant item(s) (e.g., movies to be watched, vacation packages for the next group holiday) for the whole Studies on Conformity group. A particular challenge of group recommenders is to In context of conformity, Deutsch and Gerard [9] distinguish consolidate the various—possibly contradicting—preferences informational and normative influence. Informational in- of the various group members [26, 13]. While studies inves- fluence occurs if an individual adopts the thoughts and tigating conformity typically follow a study design where attitudes from the social environment as their own [37]. participants have to decide between a correct and a wrong Frequently, the social environment is used as guidance in answer, group recommender systems operate on taste, uncertain situations [17] in an attempt to be right [38]. Nor- preferences, and relevance where none of the decisions is mative influence, in contrast, describes that an individual objectively correct or wrong. Yet, conformity in such settings expresses a particular opinion or behavior in order to fit the has not been investigated in depth. given social environment without necessarily holding that opinion or believing that the behavior is appropriate [37]. In We address this research gap and present first results of such cases, conformity is commonly based on a goal of ob- our study on conformity, which is part of our ongoing re- taining social approval [32] and motivated by an individual’s search on group recommender systems. Our online ex- attempt to fit in with a group [38]. periment where groups had to create a music playlist con- tributes to the following research question: Whether and The most influential study of conformity goes back to Asch [1, 2,3]. In his conformity experiments, a significant proportion of participants (33.3%) revised their individual judgements 30]. Studies on social media [25, 24] showcased that peo- to agree with a clearly incorrect, yet unanimous majority. ple tend to adopt the majority’s opinion on social or political Asch’s study design (i.e., a line judgement task) was used issues. A recent study [38] found that the level of confor- by an extensive number of studies (for a meta-analysis mity to the majority increased as the difference between the see [4]). Crutchfield [8] took a similar paradigm for inves- majority size and the minority size increased. A study with tigating conformity, yet removing the face-to-face situation mixed groups of human and nonhuman agents [15] found and varying the tasks to be performed (e.g., including log- different levels of conformity depending on group compo- ical tasks and expressions of attitudes). One major finding sition and task type. Carrying out a task where they had to of conformity research is that individuals tend to change judge emotions led to higher levels of conformity with the their personal judgements and opinions when challenged group opinion as the number of humans in the group in- by an opposing majority [1,4]. creased. When performing arithmetic operations, such an effect has not been observed. Studies on Conformity in Online Settings Results from studies on conformity in computer-mediated Studies on Conformity and Music scenarios vary to a great extent. When following the pro- Studies on conformity related to music preferences are cedure of Asch’s original line judgment task in a computer- scarce. Inglefield [18] (cited in [14]) found that differences mediated setting, the majority influence disappeared in an in perceived peer group membership affected changes in Sidebar 1: early study [33], whereas the conformity to a majority was preferences across musical styles. Investigating confor- Computation of Bots clearly observable in later studies, though demonstrating mity concerning music preferences, Furman and Duke [14] The decisions of the bots lower effects when compared to a face-to-face condition [6]. found that participants unfamiliar with orchestral music were were programmed in such significantly influenced by the others’ judgements, whereas a way that for the initial Furthermore, individuals from collectivistic cultures were no conformity effect was observed for participants familiar response each bot had a found to manifest greater levels of conformity than those with such music. With the same study design but for pop 30% chance to vote for a from individualistic cultures in face-to-face settings [5], music, in contrast, no such effects have been observed. song in a similar fashion whereas this effect could not be observed in a computer- as the participant and 70% mediated setting when using Asch’s study design [6]. Yet, In an online music listening setting, a study [12] found that chance against. For the online studies investigating conformity outside Asch’s paradigm feedback—irrespective of the source—significantly influ- final response, bots were found similar cultural effects to the ones observed in face- enced participants’ judgements, where feedback from other programmed with a 50/50 to-face settings. For instance, when writing online reviews, individuals was more influential than feedback allegedly chance of only changing in consumers from collectivistic cultures are less likely to devi- based on a computational analysis of the music. Another the sub-scale of their initial ate from the average prior rating in their own reviews [16]. study [10] found that popularity influence (i.e., driven by the response (i.e., yes/maybe overall popularity of an item in the whole community) and yes or no/maybe no). For the Further studies outside Asch’s paradigm have investigated proximity influence (i.e., driven by the popularity of an item bots, no complete switch in various forms of conformity in online settings. Results in- in the immediate social network of friends) are substitutes the vote happened. dicate that depersonalization and anonymity may lead to a for one another. Yet, when both are available, proximity in- more extreme perception of group norms [20] and may en- fluence dominates the effect of popularity influence. courage individuals to more strongly conform to those [29, Social Influence and Recommender Systems find songs to suggest for the playlist.
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