Abstract
Online social media is a very popular platform nowadays where people can easily make virtual connections with each other and can freely express their opinions and interests on various topics over time. The ability to freely express oneself often results in the spread of hate speech in the virtual world. Thus, it is very important to detect automatically hate speech to reduce its spread on social media. Most of the existing research works in this area paid less attention to the topical hate speech detection. In this paper, we addressed topic-oriented hate speech detection using machine learning classifiers. Experimental results on a real dataset demonstrate the efficacy of the proposed model.