Using Machine Learning to Predict the Targets of Hate Speech on Social Media

Using Machine Learning to Predict the Targets of Hate Speech on Social Media by Sahrish Altaf (2020)

Social media facilitates people having a diverse set of personalities to communicate with each other. People are free to communicate with others without any limitations. Occasionally such a communication results into use of hate speech against others. Hate speech is the use of violent, aggressive, and offensive language. Though social media websites do not allow the use of hate speech, but the size of these platforms makes it nearly impossible to manage all their content. Consequently, several studies have been conducted for automatically detecting hate speech on social media. Focus of these studies is to detect the hateful content. Majority of these studies ignore predicting the tar- get of the hate speech on social media. Focus of this study is to predict targets of hate speech. In this regard, firstly, a new balanced Hate Speech Targets Dataset (HSTD) is developed. HSTD contains tweets labeled for targets and non-targets of hate speech. Secondly, a novel framework Hate–speech Targets Prediction FrameworK (HTPK) is pro- posed to predict the targets of hate speech on social media. Comparison with state-of- the-art methods shows that HTPK performs better than these methods.