Youths of the digital age live parallel lives online and in the real world, frequently disclosing personal information to cyberfriends and strangers, regardless of race, class or gender. Race and gender do make a difference, however, when these online disclosures lead to acts of cyberaggression. The PIs' previous work revealed that some youths are resistant to cyberaggression and that there are differences in perceptions of cyberbullying among youths from different cultural and racial backgrounds. This research aims to explore the relationship between youths' self-disclosures, cultural backgrounds, and their perceptions of cyberaggression.
The PIs conduct a longitudinal, interdisciplinary study that builds upon their ongoing cyberaggression pattern recognition research by: 1) using surveys and focus groups to test and refine their theories about self-disclosure, perception, cultural difference, and cyberaggression communication patterns, 2) using machine learning to develop detection and response technologies for use in applications designed to protect youths, 3) using focus groups to evaluate the applications, and 4) making the data collected from this project available to the research community. This work is important to understand the role of self-disclosure in cybervictmization among youths, and provides the theoretical groundwork for the development of effective response strategies that can be employed by youths when they are attacked online. The data from this study will provide a rich source of material for other researchers in both computer science and in the social and behavior sciences.
