Detection of Hate Speech and Offensive Language Using Machine Learning and Deep Learning for Multi-Class Tweets

Nowadays, every single person is indulged in social media, and because of its hidden characteristics, people are free to express their views and thoughts and expressing their views freely is their right. Expressing their thoughts and views on dynamic news puts a positive impact in economy, as it shows how people relate to each other. Yet, there are times when individuals throw toxic comments or accusing them on the grounds of caste, religion, gender identity, ethnicity etc. is a harassment of the given freedom. Due to this, hate and offensive language has become the serious issue, in modern society, which leads to damaging the people's peace, their human rights as well as creating an inequality in society. In this research paper, the dataset has been taken from the Kaggle source, sentiment analysis will be done on the detection of hate speech and offensive language, and the classification will be done on the following three labels: Hate Speech, Offensive Language and Neither.