Antisocial Behavior in Online Discussion Communities
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.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Spillover of Antisocial Behavior from Fringe Platforms: The Unintended Consequences of Community Banning
Online platforms face pressure to keep their communities civil and respectful. Thus, the bannings of problematic online communities from mainstream platforms like Reddit and Facebook are often met with enthusiastic publi…
On Analyzing Antisocial Behaviors Amid COVID-19 Pandemic
The COVID-19 pandemic has developed to be more than a bio-crisis as global news has reported a sharp rise in xenophobia and discrimination in both online and offline communities. Such toxic behaviors take a heavy toll on…
Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations
Online conversations can go in many directions: some turn out poorly due to antisocial behavior, while others turn out positively to the benefit of all. Research on improving online spaces has focused primarily on detect…
Conversations Gone Awry: Detecting Early Signs of Conversational Failure
One of the main challenges online social systems face is the prevalence of antisocial behavior, such as harassment and personal attacks. In this work, we introduce the task of predicting from the very start of a conversa…
Improving Moderation of Online Discussions via Interpretable Neural Models
Growing amount of comments make online discussions difficult to moderate by human moderators only. Antisocial behavior is a common occurrence that often discourages other users from participating in discussion. We propos…