Hateful Speech Detection in Public Facebook Pages for the Bengali Language
Alvi Md. Ishmam, Sadia Sharmin · 2019
Online hateful speech detection and classification in social media for the various major languages other than English has drawn the attention of researchers recently. In this paper, we develop Machine Learning (ML) algorithms based model, as well as Gated Recurrent Unit (GRU), based deep neural network model for classifying users' comments on Facebook pages. We have collected, annotated 5,126 Bengali comments and classified them into six classes - Hate Speech, Communal Attack, Inciteful, Religious Hatred, Political Comments, and Religious Comments. The produced corpus is the first contribution to the field of hateful speech detection in the Bengali language for social media. Finally, we employ several machine learning algorithms, compare the performance, and attained 52.20% accuracy in Random Forest. The accuracy is improved in the case of GRU based model (70.10% accuracy) about 18%.