Paper: Learning from Bullying Traces in Social Media

ACL ID N12-1084
Title Learning from Bullying Traces in Social Media
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2012

We introduce the social study of bullying to the NLP community. Bullying, in both physi- cal and cyber worlds (the latter known as cy- berbullying), has been recognized as a seri- ous national health issue among adolescents. However, previous social studies of bully- ing are handicapped by data scarcity, while the few computational studies narrowly re- strict themselves to cyberbullying which ac- counts for only a small fraction of all bullying episodes. Our main contribution is to present evidence that social media, with appropriate natural language processing techniques, can be a valuable and abundant data source for the study of bullying in both worlds. We iden- tify several key problems in using such data sources and formulate them as NLP tasks, in- cluding text classification, role la...