Cyberbullying Detection in Social Media Using Supervised Machine Learning Techniques

Abstract

With the increasing use of social media platforms such as Facebook, Twitter and Instagram, more and more people are connecting with each other throughout the world. People use these social media platforms to express their individuality, thoughts, ideas and opinions freely. However, a certain group of people abuse this freedom of speech to offend others. This is called cyberbullying. Some common examples of cyberbullying are posting derogatory or offensive comments, expressing hostility or aggression online, spreading false rumors, creating fake IDs etc. In this paper, we propose the use of Supervised Machine Learning techniques to find an efficient labeling method for effectively predicting and detecting cyberbullying in social media sites through comparative analysis.