Attention-based networks for analyzing inappropriate speech in Arabic text
Analyzing social media posts and comments has become a critical task to prevent cyberbullying and hate speech. In this work we present a classification models based on the attention mechanism to analyze Arabic posts and filter out all kinds of inappropriate speech including Religious based hate speech, offensive and abusive content in different Arabic dialects. The attention-based models show promising results for four Arabic datasets. The results are presented and compared in terms of accuracy and training time.