Automatic Hate Speech Detection on Social Media: A Brief Survey

Abstract

Due to the advancement in technology and the explosion of the information age, people communicate with each other indirectly via using the online social networks (OSNs), such as Facebook Snapchat, Instagram, and Twitter. Users of OSNs can post anything without any control or constraint of the content, which leads to increase in spreading of hateful and offensive speech among users, thus resulting in an increase in crimes, murder, and terrorism. Hence, this paper provides a survey and state of the art natural language processing (NLP) technique that is used in automatic detection of the hate speech on OSNs, such as dictionaries, bag-of-words, N-gram etc.