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The present analyses empirically explored the roles in cyberbullying by using Latent Class Analysis. Potential predictors of class membership were also examined using multinomial logistic regression analysis. Participants were 849 German students (52.7% girls, 45.6% boys, M age = 13.4 years, SD age = 1.1 years). Observed indicators of latent class measured own involvement in cyberbullying, reactions to cyberbullying of classmates, and behavioral willingness as assistant and as defender. Indicators for the post-hoc regression analyses were proactive aggression, reactive aggression, self-esteem, cognitive, and affective empathy. Control variables were age and gender. A model with five classes was chosen. The classes were labeled prosocial defenders, communicating outsiders, aggressive defenders, bully-victims, and assistants. The results of the post-hoc regression analyses showed that students in the classes especially differed regarding types of aggression and social competencies. Based on answer patterns, cyberbullying roles beyond the bullying-triad can be found. Remarkably, three of the classes are bystanders, i.e. they are not directly involved in cyberbullying. Two of these classes showed helping behavior and made up almost two thirds of the sample. Knowledge about cyberbullying roles and their predictors is important to inform the planning and development of interventions. The results further indicate that interventions should especially take into account antisocial and passive behavioral patterns in the context of cyberbullying.

Who is involved in cyberbullying? Latent class analysis of cyberbullying roles and their associations with aggression, self-esteem, and empathy