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Extracting Inter-Community Conflicts in Reddit Proceedings of the Thirteenth International AAAI Conference on Web and Social Media (ICWSM 2019) Extracting Inter-Community Conflicts in Reddit Srayan Datta Eytan Adar University of Michigan University of Michigan [email protected] [email protected] Abstract sult is an entire embedded network of subreddit-to-subreddit conflicts inside of the Reddit ecosystem. Research has found Anti-social behaviors in social media can happen both at user specific instances of these conflicts. Our goal is to inferen- and community levels. While a great deal of attention is on the individual as an ‘aggressor,’ the banning of entire Red- tially identify the structure and dynamics of this community- dit subcommunities (i.e., subreddits) demonstrates that this is to-community conflict network at scale. a multi-layer concern. Existing research on inter-community To achieve this, we address a number of challenges. First conflict has largely focused on specific subcommunities or among them is the lack of explicit group membership. Group ideological opponents. However, antagonistic behaviors may ‘membership’ in Reddit, and systems like it, can be vague. be more pervasive and integrate into the broader network. In While subscriptions are possible, individuals can display this work, we study the landscape of conflicts among sub- member-like behaviors by posting to subreddits they are reddits by deriving higher-level (community) behaviors from not part of. Such behaviors—subscription and posting—are the way individuals are sanctioned and rewarded. By con- structing a conflict network, we characterize different patterns not, however, a clear indication of the individual’s ‘social in subreddit-to-subreddit conflicts as well as communities of homes.’ An individual can display both social and anti-social ‘co-targeted’ subreddits .The dynamics of these interactions behaviors within the community via posting. What we seek also reveals a shift in conflict focus over time. 1 is not simply identifying an individual’s ‘home’ but to also discriminate between social homes and anti-social homes. To achieve this separation, we apply a definition that ex- Introduction tends Brunton’s construct of spam (Brunton 2012): a com- Anti-social behavior in social media is not solely an indi- munity defines spam as (messaging) behavior that is not con- vidual process. Communities can, and do, antagonize other sistent with its rules and norms. That is, we seek to separate groups with collective anti-social behaviors. Similarly, both norm-complaint behaviors that indicate social membership individuals and communities can be sanctioned in reaction and those that are norm-violating (indicating an anti-social to this behavior. On Reddit, for example, individuals can be home). Rather than relying on a global definition of norms, banned or otherwise penalized (e.g., have their posts down- we utilize the sanctioning and rewarding behavior of individ- voted). Likewise, entire subreddits can also be sanctioned ual subreddits in response to norm violation and compliance when multiple individuals violate general Reddit norms and respectively. An explicit measure we leverage is up- and use the community as a platform for generating conflict. down-voting on posted comments. While these are not the Critically, the form of anti-social behavior at the com- only sanctions and rewards, they are (a) consistently used, munity level can be quite varied. The ability to identify and (b) can be aggregated both at the individual and com- and coordinate with others means that actions considered munity levels. As we demonstrate below, inference based on anti-social for the individual can be expanded to group set- these lower level signals can help identify broader conflicts. tings. A group can thus act anti-socially— producing mass A further appeal of the bottom-up approach is that the spamming, trolling, flame wars, griefing, baiting, brigading, converse, top-down identification of sanctions at the subred- fisking, crapflooding, shitposting, and trash talking—against dit level, does not provide a clear indication of conflict. First, both individuals and other subreddits (Kumar et al. 2018). this signal is sparse as the banning of subreddits remains On Reddit, as in other discussion boards, the ability to create rare. Except for explicit brigading, which are (hard to de- (multiple) accounts under any pseudonym can further exac- tect) coordinated attacks on another subreddit, community- erbate such behaviors. Although a vast majority of users are based anti-social behaviors may not result in a community generally norm-compliant, anonymity can lead to less inhib- being visibly sanctioned. Second, even when a sanction is ited behavior from users (Suler 2004). In aggregate, the re- employed it may be due to other reasons than community- Copyright c 2019, Association for the Advancement of Artificial on-community attacks. For example, subreddits such as fat- Intelligence (www.aaai.org). All rights reserved. peoplehate (a fat-shaming subreddit) and europeannational- 1The network datasets from our study are publicly available at ism (a racist subreddit) have been banned, not necessarily https://github.com/srayandatta/Reddit conflictgraph. due to any specific ‘attack,’ but rather non-compliance with 146 Reddit-wide norms on hate speech. Related Work Our bottom-up inference is different in that we can iden- Conflicts in Social Media tify pairs of social and anti-social homes and aggregate these to find conflicts. Specifically, we can find authors implicated Undesirable behavior in online communities are widely in conflicts—which we call controversial authors—by iden- studied in social media research. Qualitative analysis of- tifying those that have both social and anti-social homes. ten focuses on identifying and characterizing different types From this, we can say that if multiple authors have a social- of inappropriate online behaviour or provides case studies home in subreddit A and an anti-social home in subreddit B, in different forums. Analysis of Usenet news, for example, then there is a directed conflict between A and B. By find- helped explore identity and deception (Donath 1999). Gen- ing aggregate patterns using all Reddit comments from 2016 eral anti-social behaviors (Hardaker 2010) can also mani- (9.75 million unique users and 743 million comments), we fest in ‘site-specific’ ways as in the trolling and vandals on can construct the subreddit conflict graph at scale. Further- Wikipedia (Shachaf and Hara 2010), or griefing and com- more, we demonstrate how directed edges in our graph can bative strategies in Second Life (Chesney et al. 2009). be weighted as a measure of conflict intensity. The process Predicting trolls and other anti-social behavior is another of identifying conflict edges and their associated weights well explored research area. For example, researchers have is complicated by inherent noise in behaviors and high- identified a connection between trolling and negative mood variance of community sizes. A specific contribution of our which provided evidence for a ‘feedback’ loop that con- work is the use of different aggregation and normalization tributes to further trolling (Cheng et al. 2017). In the con- techniques to more clearly identify the conflict graph. text of prediction, several studies focused on detecting cer- Using this graph, we can determine not only the broad tain anti-social behaviors on specific sites (e.g., vandalism landscape of community-to-community conflicts but to an- in Wikipedia (Adler et al. 2011; Kumar, Spezzano, and Sub- swer specific questions as well: Which subreddits are most rahmanian 2015)). Others have attempted to predict both often instigators of conflict (versus targets)? Are conflicts re- anti-social behaviors or sanctions. Examples of the former ciprocal and are they proportional in intensity? Does ‘attack- include finding sockpuppets (same user with multiple ac- ing’ multiple subreddits imply broad member misbehavior counts) on discussion sites (Kumar et al. 2017) and Twit- or the work of just a few individuals? Are certain subreddits ter (Galan-Garc´ ´ıa et al. 2013). Within Reddit, Kumar et targeted ‘together?’ Do conflicts shift over time? al. (Kumar et al. 2018) studied controversial hyperlink cross- Briefly, we find that subreddit conflicts are often recipro- postings between subreddits to identify community conflict. cal, but the conflict intensity is weakly negatively correlated Examples of the latter (sanction prediction) include banning with the intensity of the ‘response.’ We also find the larger prediction based on comments (Cheng, Danescu-Niculescu- subreddits are more likely to be involved in a large number Mizil, and Leskovec 2015) and using abusive content on of subreddit conflicts due to their size. However, our anal- one forum to predict abuse on others (Chandrasekharan et ysis of the fraction of users involved can isolate situations al. 2017b). The bulk of this research emphasized individ- where both relative and absolute counts of involved authors ual behavior rather than inter-community anti-social behav- are high. Additionally, we find different patterns of conflict ior (rare exceptions emphasized specific types of anti-social based on intensity. For example, a single subreddit targeting behavior). While we draw upon this literature to under- many others may divide its attention, resulting in decreased stand individual behaviors, we focus on a broad definition intensity across the targets. On the other hand, we find anec- of higher-order inter-community conflicts. That is, our aim
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