Detecting and Tracking Cyber Bullying on the Social Web









As many children are connected to their peers and spend a significant amount of time on social web sites (Facebook, Twitter, etc.), cyber bullying in social media is becoming a severe problem that can lead to serious social, psychological, and health effects. To alleviate the problem, intervention from adults (teachers, parents, law enforcement, social web site moderators, etc.) is the key. However, many victims do not report bullying to adults, and bullies can use aliases and act anonymously, and thus they are difficult to identify. The goal of this exploratory project is to eliminate or at least reduce these problems by developing an intelligent system to automatically detect and track cyber bullies on the social web.

This project explores a solution to cyber bullying based on a combination of machine learning, natural language processing, information filtering, and recommendation and social network modeling techniques.

This material is based upon work supported by the National Science Foundation under Grant IIS-1144564. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.