Detecting Hate Speech in Social Media Articles in Romanized Sinhala

The main aim of this research is to automatically identify the hate content of social media comments and documents written by the Romanized Sinhala Language. Also most of researched done the hate speech recognition study in English or their language but here identify the Sinhala words that's written in English letters that means Romanized Sinhala language. Hate words and other hated texts are growing issue, and to combat this they turn to machine learning and computer science. In this research compare the several features extraction method and four machine learning algorithms and difference N-gram values unigram, bigram and trigram and used the Min-Df value 3. This study will investigate and compare different features for the different classifier when classifying hate speech comments on Facebook. We have achieved a data set of nearly 2500 comments, some containing hate speech, and trained and tested our classifier with different features.