A systematic review proposes a five-part taxonomy for antisocial behavior prediction, covering early harm detection, harm emergence, propagation, behavioral risk, and proactive moderation.
Characterizing Engagement Dynamics across Topics on Facebook
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abstract
Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users' polarization. We perform a quantitative analysis on Facebook by collecting $\sim57M$ posts from $\sim2M$ pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users' future adverse reactions regardless of the discussed topic.
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Before the Outrage: Challenges and Advances in Predicting Online Antisocial Behavior
A systematic review proposes a five-part taxonomy for antisocial behavior prediction, covering early harm detection, harm emergence, propagation, behavioral risk, and proactive moderation.