Real-Time Detection of Cyberbullying in Arabic Twitter Streams

Abstract

Cyberbullying is a form of psychological abuse, which is very dangerous as the victims of cyberbullying, especially children and teenagers, suffer from many mental issues that could lead to suicide thoughts. Cyberbullying is also becoming a significant issue in the Middle East. Existing contributions for cyberbullying detection focus mainly on English language. This paper presents an approach to detect cyberbullying in Arabic Twitter streams in real-time. In addition, it classifies the bullying messages based on their strength. In case a cyberbullying message is detected, the system notifies the user and proposes a set of actions to take based on the strength of the bullying message. We demonstrate the relevance of the proposed approach by showing how it could be used by a parent to monitor his kids' activities and get notified in case a suspicious activity is detected. The experiments show that the proposed system was able to effectively identify the cyberbullying messages in near real-time.