Hate Speech Classification Using Machine Learning

Hate speech is a crime that has increased recently, both online and in face-to-face interactions. There are several reasons for this. On the one hand, people are more prone to act hostilely because of the anonymity provided by the internet, and social networks in particular. On the other hand, people’s urge to express their opinions online has grown, which has contributed to the proliferation of hate speech. Given how damaging this kind of discriminatory speech can be to society, governments and social media companies can both profit from detection and prevention strategies. Through this survey, we provide a thorough evaluation of the research conducted in the field, which helps to resolve this conundrum.The use of many complex and non-linear models helped with this difficulty, and CAT Boost outperformed the others because it applied latent semantic analysis (LSA) to reduce dimensionality.