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aiXplain at Arabic Hate Speech 2022: An Ensemble Based Approach to Detecting Offensive Tweets

2022-06-01 · OSACT (LREC) 2022 6 · Salaheddin Alzubi, Thiago castro Ferreira, Lucas Pavanelli, Mohamed Al-Badrashiny

Abusive speech on online platforms has a detrimental effect on users’ mental health. This warrants the need for innovative solutions that automatically moderate content, especially on online platforms such as Twitter where a user’s anonymity is loosely controlled. This paper outlines aiXplain Inc.’s ensemble based approach to detecting offensive speech in the Arabic language based on OSACT5’s shared sub-task A. Additionally, this paper highlights multiple challenges that may hinder progress on detecting abusive speech and provides potential avenues and techniques that may lead to significant progress.

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