The Different Structure and Predictors of Online Aggression and Offline Aggression: A Network Analysis Approach

Online aggression is a serious social problem in the Internet era, which seriously threatens the physical and mental health of individuals. Exploring how online aggression differs from offline aggression can help us develop targeted prevention and intervention measures. However, the basic difference between online aggression and traditional offline aggression remains unclear. This study tried to address the issues from the perspective of structure and predictors by using network analysis in 1,009 Chinese college students. The dimensions of online and traditional offline aggression were utilized to detect the community. And incorporate individual and situational predictors as nodes for network analysis. The results showed that the nodes of Cyber-Aggression Typology Questionnaire and Buss Perry Aggression Questionnaire were divided into two distinct communities. The edge-weight bootstrapped difference test showed that callous-unemotional traits, trait anger, empathy, and guilt were only associated with offline aggression. Furthermore, moral disengagement and social exclusion were more closely associated with offline aggression than online aggression, while violent attitude was more associated with online aggression. These findings support and expand the Barlett and Gentile Cyberbullying Model, enhancing our comprehension of both offline and online aggression, and providing inspiration for prevention and intervention in offline and online aggression in the future.