Abstract
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).- Anthology ID:
- 2020.osact-1.10
- Volume:
- Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Venue:
- OSACT
- SIG:
- Publisher:
- European Language Resource Association
- Note:
- Pages:
- 66–70
- Language:
- English
- URL:
- https://aclanthology.org/2020.osact-1.10
- DOI:
- Cite (ACL):
- Amr Keleg, Samhaa R. El-Beltagy, and Mahmoud Khalil. 2020. ASU_OPTO at OSACT4 - Offensive Language Detection for Arabic text. In Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection, pages 66–70, Marseille, France. European Language Resource Association.
- Cite (Informal):
- ASU_OPTO at OSACT4 - Offensive Language Detection for Arabic text (Keleg et al., OSACT 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.osact-1.10.pdf