ASU\_OPTO at OSACT4 - Offensive Language Detection for Arabic text

2020-05-01 · LREC 2020 5 · Amr Keleg, Samhaa R. El-Beltagy, Mahmoud Khalil

In the past years, toxic comments and offensive speech are polluting the internet and manual inspection of these comments is becoming a tiresome task to manage. Having a machine learning based model that is able to filter offensive Arabic content is of high need nowadays. In this paper, we describe the model that was submitted to the Shared Task on Offensive Language Detection that is organized by (The 4th Workshop on Open-Source Arabic Corpora and Processing Tools). Our model makes use transformer based model (BERT) to detect offensive content. We came in the fourth place in subtask A (detecting Offensive Speech) and in the third place in subtask B (detecting Hate Speech).

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