Despite many benefits, one consequence of technology's proliferation and ritualized use is cyberbullying or digital aggression (DA). One key theory for understanding DA is the General Aggression Model. This model proposes that DA can be best understood as a consequence of interactions between personal and situational factors. Consistent with this theory, personality and anonymity have been identified as independent predictors of DA. Critically, however, virtually no research has sought to investigate whether and how these two factors may interact in predicting DA. The first study sought to bridge this gap by coding real-world DA behaviors on Twitter. Our findings indicated that individuals high in intellect/imagination used more antisocial words when they had anonymous Twitter accounts but not identifiable ones. The second study examined the effects of personality and technical self- and other-anonymity, including their interactions, on DA using a recently developed in-vivo experimental paradigm, the TAP-Chat. We found that anonymity moderated the relationship between extraversion and in-vivo DA, such that individuals high in extraversion used more antisocial words during the experiment when the participant and co-player were fully identified compared to when both were fully anonymous. Our findings collectively illuminate the roles of personality and anonymity in the prevalence of DA while indicating that these associations are measure- and context-specific. Such findings have key implications for the field's understanding of DA and, in doing so, inform the development of policy and prevention and intervention programs for DA.
Read
