A Comparative Study of Cyberbullying Detection in Social Media for the Last Five Years

Abstract

    The number of users of social media sites has increased nowadays, and while these sites have many benefits, they also have many damages that have grown with the increasing number of users. Among these damages that have spread in social media sites in our time is the phenomenon of cyberbullying. It has become necessary to find solutions to detect it to prevent and hold bullies accountable to reduce the phenomenon of cyberbullying, which has great health and mental effects on the victim in society. There have been many attempts to build models to detect and classify cyberbullying by using machine learning and deep learning algorithms with different sets of data that were collected from social media sites such as Twitter, YouTube, Facebook, Instagram, and others. In this work, we show a group of previous studies that used machine learning and deep learning algorithms in good attempts to detect and classify the phenomenon of cyberbullying.