Abstract
The rapid development of online communication and information sharing platforms and the enthusiastic participation of their users have enabled peer-to-peer communication at unprecedented scale and diversity. On one hand, this communication channels, such as online social networks and news sharing websites, offer myriad opportunities for knowledge sharing and opinion mobilization. On the other hand, they also serve as a fertile domain for an abundance of unfortunate intimidation and hateful aggression and cyberbullying towards individuals targeted because of their identities or expressed opinions. In this thesis we have proposed an ensemble approach towards the detection of cyberbullying using machine learning techniques.