A novel in vivo measure of cyberaggression.

Abstract

Cyberaggression (CA), or the use of information communication technologies to inflict harm on others, is an emerging public health crisis. Unfortunately, our current ability to assess CA in a research context remains limited, curtailing efforts to address this important issue. We sought to fill this gap in the literature by developing an adapted "chat" version of the Taylor aggression paradigm (TAP) that would more closely resemble a social gaming format (hereafter referred to as the TAP-Chat). In the TAP-Chat, participants have a chat function available to communicate with their (fictitious) co-player. Following loss trials in a competitive reaction time task, they receive a "mean chat" from their co-player. Participant messages to their (fictitious) co-player are then coded for aggressive content by a team of trained research assistants, and via automated linguistic analysis software (Linguistic Inquiry and Word Count). The current study evaluated the predictive utility of the TAP-Chat task in independent discovery and replication samples (N = 843 and N = 350, respectively). Participants' publicly available tweets served as an important external criterion variable, along with a handful of self-report questionnaires assessing CA and related constructs. Analyses suggest that, although it can be completed in ∼13 min, the TAP-Chat predicts CA on Twitter and, to a lesser extent, as reported on questionnaires. Although there are still several issues to address, it is our hope that the research community will benefit from this straightforward behavioral assessment of CA.