Abstract

Modern young people (�digital natives�) have grown in an era dominated by new technologies where communications are pushed to quite a real-time level, and pose no limits in establishing relationships with other people or communities. The fast growing use of social networking sites among the teens have made them vulnerable to get exposed to bullying. Comments containing abusive words effect psychology of teens and demoralize them. In this work we have devised methods to detect cyber bullying using supervised learning techniques. Cyber bullying is the use of technology as a medium to bully someone. Although it has been an issue for many years, the recognition of its impact on young people has recently increased. Through machine learning, we can detect language patterns used by bullies and their victims, and develop rules to automatically detect cyber bullying content. The data we used for our work was collected from the website kagle.com; it contains a high percentage of bullying content

Description