A Systematic Literature Review of Different Machine Learning Methods on Hate Speech Detection

Abstract

Hate speech is one of the most challenging problem internet is facing today. This systematic literature review examine hate speech detection problem and will be used to do an experimental approach on detecting hate speech and abusive language. This work also provide an overview of previous research, including methods, algorithms, and main features used. We use two research questions in this literature review which will be the foundation of the next experimental research. Correctly classifying a piece of text as an actual hate speech requires a lot of correctly labelled data. Most common challenges are different languages, out of vocabulary words, long range dependencies and many more.