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Cyberbullying is the most common online risk for adolescents, yet the majority of young people who are bullied online do not tell their parents when it occurs. The goal of the BullyBlocker project is to advance the understanding of how cyberbullying, in particular, and behavioral issues, more broadly, can be effectively identified on social networking sites. This interdisciplinary project integrates advances in computer sciences and key findings from psychological research on cyberbullying to (i) design and implement models for identifying cyberbullying on social networking platforms, and (ii) study usage patterns of automated tools based on these models and their utility for devising and testing new hypotheses about cyberbullying risk factors.
The intellectual merit of this project stems from its synergistic integration of computer and psychological science to address a social problem that negatively impacts adolescents, their families, and society. The project draws on psychological research on cyberbullying risk factors and advances in computer science to enable the development of automated identification models and the integration of these models into an app (BullyBlocker) that notifies parents about their adolescents' risk of cyberbullying. The project also entails the design of mechanisms to generate customized anti-bullying resources for parents and victims, investigation of app usage patterns and parents' attitudes towards automated identification tools, the use of automated tools such as BullyBlocker to devise and test new hypotheses about cyberbullying, and a unique training opportunity that provides graduate and undergraduate students with the scientific scaffolding to develop into recognized interdisciplinary scholars.
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EAGER: BullyBlocker - Identifying Cyberbullying in Social Networking Sites