Trolling is a subject of apparent academic confusion; the few studies conducted thus far yielded a variety of conflicting definitions regarding what constitutes trolling behaviour and little information regarding trolling motivations. In order to shed further light on this phenomenon, the present study aimed to (1) determine which behaviours actual trolls consider as trolling, (2) explore the motivations behind trolling, and (3) examine the online community's response to trolling as perceived by the troll. After performing semi-structured interviews with 22 self-confessed trolls, we found that there is a variety of behaviours trolls consider trolling which can now be put in clear categories based on target and method. Three key motivations to troll emerged: personal enjoyment, revenge, and thrill-seeking. Trolling also appears to be a cyclical, self-perpetuating phenomenon enabled by the online community at large. Theoretical implications for future trolling research are also discussed. KeywordsInterviews, motivation, trolling, online community, online gamesIn the world of online gaming, undesirable behaviour is commonplace. Players will kill teammates, verbally abuse their peers, and misdirect new community members, spreading chaos and disorder (see Riot Games, 2015). These people are called 'trolls'

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Dijksterhuis and van Knippenberg (1998) reported that participants primed with a category associated with intelligence ("professor") subsequently performed 13% better on a trivia test than participants primed with a category associated with a lack of intelligence ("soccer hooligans"). In two unpublished replications of this study designed to verify the appropriate testing procedures, Dijksterhuis, van Knippenberg, and Holland observed a smaller difference between conditions (2%-3%) as well as a gender difference: Men showed the effect (9.3% and 7.6%), but women did not (0.3% and -0.3%). The procedure used in those replications served as the basis for this multilab Registered Replication Report. A total of 40 laboratories collected data for this project, and 23 of these laboratories met all inclusion criteria. Here we report the meta-analytic results for those 23 direct replications (total N = 4,493), which tested whether performance on a 30-item general-knowledge trivia task differed between these two priming conditions (results of supplementary analyses of the data from all 40 labs, N = 6,454, are also reported). We observed no overall difference in trivia performance between participants primed with the "professor" category and those primed with the "hooligan" category (0.14%) and no moderation by gender.

The present study aimed to expand our understanding of trolling interactions by examining 10,025 community-reported trolling incidents in the online game League of Legends to determine what characterizes messages sent by trolls, their teammates, and their opponents. To do this, we used a novel method blending content analysis and topic modelling. Contrary to extant literature, our study of complete trolling interactions found striking similarities between teammates’ and trolls’ chats, with both displaying the negative traits (e.g., exclusionary language) typically attributed to trolls. Findings also suggest that the transition from victim to perpetrator can occur extremely rapidly. This has important implications for the labelling of actors in trolling interactions, for future studies into the trolling cycle, and for theories of computer-mediated communication.