ARHNet-Leveraging Community Interaction for Detection of Religious Hate Speech in Arabic

Abstract

The rapid widespread of social media has lead to some undesirable consequences like the rapid increase of hateful content and offensive language. Religious Hate Speech, in particular, often leads to unrest and sometimes aggravates to violence against people on the basis of their religious affiliations. The richness of the Arabic morphology and the limited available resources makes this task especially challenging. The current state-of-the-art approaches to detect hate speech in Arabic rely entirely on textual (lexical and semantic)

Publication
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop

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