| Literature DB >> 29399664 |
Justin Cheng1, Michael Bernstein1, Cristian Danescu-Niculescu-Mizil2, Jure Leskovec1.
Abstract
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.Entities:
Keywords: H.2.8 Database Management: Database Applications–Data Mining; J.4 Computer Applications: Social and Behavioral Sciences; Trolling; antisocial behavior; online communities
Year: 2017 PMID: 29399664 PMCID: PMC5791909 DOI: 10.1145/2998181.2998213
Source DB: PubMed Journal: CSCW Conf Comput Support Coop Work