Litcius/Paper detail

Antisocial Behavior in Online Discussion Communities

Justin Cheng, Cristian Danescu-Niculescu-Mizil, Jure Leskovec

2021Proceedings of the International AAAI Conference on Web and Social Media210 citationsDOIOpen Access PDF

Abstract

User contributions in the form of posts, comments, and votes are essential to the success of online communities. However, allowing user participation also invites undesirable behavior such as trolling. In this paper, we characterize antisocial behavior in three large online discussion communities by analyzing users who were banned from these communities. We find that such users tend to concentrate their efforts in a small number of threads, are more likely to post irrelevantly, and are more successful at garnering responses from other users. Studying the evolution of these users from the moment they join a community up to when they get banned, we find that not only do they write worse than other users over time, but they also become increasingly less tolerated by the community. Further, we discover that antisocial behavior is exacerbated when community feedback is overly harsh. Our analysis also reveals distinct groups of users with different levels of antisocial behavior that can change over time. We use these insights to identify antisocial users early on, a task of high practical importance to community maintainers.

Topics & Concepts

Task (project management)Online communityComputer sciencePsychologyInternet privacyOnline discussionWorld Wide WebEngineeringSystems engineeringHate Speech and Cyberbullying DetectionSocial Media and PoliticsSpam and Phishing Detection