2017/02/03 by Justin Cheng, Michael S. Bernstein, Michael Bernstein +2 · 1 voice · 482 citations
Computer Science · Mathematics · Physics and Astronomy · Psychology · Social Sciences · #Cognitive psychology #Computer science #Constructive #Context (archaeology) #Hate Speech and Cyberbullying Detection #Mood #Opinion Dynamics and Social Influence #Process (computing) #Psychology #Social Media and Politics #Social psychology #cs.CY #cs.HC #cs.SI #stat.AP
paper · pdf · doi:10.1145/2998181.2998213
Best Paper Award at CSCW 2017
arxiv created 2017/02/03 · arxiv published 2017/02/03 · arxiv updated 2017/02/07 · openalex publication_date 2017/02/14 · openalex created_date 2017/02/24 · openalex updated_date 2026/08/05
In online communities, antisocial behavior such as trolling disrupts constructive discussion. While prior work suggests that trolling behavior is confined to a vocal and antisocial minority, we demonstrate that ordinary people can engage in such behavior as well. We propose two primary trigger mechanisms: the individual's mood, and the surrounding context of a discussion (e.g., exposure to prior trolling behavior). Through an experiment simulating an online discussion, we find that both negative mood and seeing troll posts by others significantly increases the probability of a user trolling, and together double this probability. To support and extend these results, we study how these same mechanisms play out in the wild via a data-driven, longitudinal analysis of a large online news discussion community. This analysis reveals temporal mood effects, and explores long range patterns of repeated exposure to trolling. A predictive model of trolling behavior shows that mood and discussion context together can explain trolling behavior better than an individual's history of trolling. These results combine to suggest that ordinary people can, under the right circumstances, behave like trolls.