Cyber reactive aggression (CRA) among college students is a prevalent and harmful phenomenon. Psychological characteristics, such as trait anger (TA), hostile attribution bias (HAB), and revenge motivation (RM), are known to contribute to reactive aggression. However, the interactions between these factors in the context of cyberspace and their contribution to CRA among college students have not been extensively studied. This cross-sectional study aimed to identify the associations among psychological characteristics, demographic factors, and CRA among Chinese college students through Mixed Graphical Model (MGM) network and mediation effect analyses. A total of 926 participants completed questionnaires assessing TA, HAB, RM, and CRA. The study found both direct and indirect relationships between TA and CRA, with HAB and RM serving as mediating factors. Comparisons indicated that HAB had a more significant impact on the three indirect effects than RM. Furthermore, gender was found to be associated with TA and CRA, while the left-behind experience strongly influenced HAB but had no association with other variables. This study highlights the importance of considering psychological characteristics and demographic factors in understanding CRA among college students, suggesting that effective psychological interventions, such as anger management, and promoting positive attribution training, may help reduce CRA among college students and inform the development of targeted interventions to reduce cyber aggression.
Keywords: cyber reactive aggression; hostile attribution bias; network analysis; revenge motivation; trait anger.