Automatic Detection of Cyberbullying and Abusive Language in Arabic Content on Social Networks: A Survey
Marwa Khairy, Tarek M. Mahmoud, Tarek Abd El‐Hafeez
Abstract
As a key player in today’s world, online social networks are emerging, providing a platform for expression and content distribution. This technology enables users to communicate easily with each other and share their data instantly. However, the internet isn’t generally protected; it can be a source for abusive and harmful content and causing harm to others. There is a great need for approaches and strategies to solve these issues due to the negative effect of abusive language and cyberbullying. Arabic text is known for its challenges, complexity, and scarcity of its resources. Many languages have made many efforts to find automated solutions for detecting abusive language and cyberbullying, but not much for the Arabic language. This work analyzes 27 studies on automatic Arabic abusive language and cyberbullying and its related detection approaches. The goal of this paper is to review the findings of the previous studies about cyberbullying and abusive detection in Arabic content on online social networks and help researcher in the future to develop automatic detection systems that are effective and realistic.