ALT Submission for OSACT Shared Task on Offensive Language Detection
Sabit Hassan, Younes Samih, Hamdy Mubarak, Ahmed Abdelali, Ammar Rashed, Shammur Absar Chowdhury
Abstract
In this paper, we describe our efforts at OSACT Shared Task on Offensive Language Detection. The shared task consists of two subtasks: offensive language detection (Subtask A) and hate speech detection (Subtask B). For offensive language detection, a system combination of Support Vector Machines (SVMs) and Deep Neural Networks (DNNs) achieved the best results on development set, which ranked 1st in the official results for Subtask A with F1-score of 90.51% on the test set. For hate speech detection, DNNs were less effective and a system combination of multiple SVMs with different parameters achieved the best results on development set, which ranked 4th in official results for Subtask B with F1-macro score of 80.63% on the test set.- Anthology ID:
- 2020.osact-1.9
- 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
- Venues:
- LREC | OSACT | WS
- SIG:
- Publisher:
- European Language Resource Association
- Note:
- Pages:
- 61–65
- URL:
- https://www.aclweb.org/anthology/2020.osact-1.9
- DOI:
- PDF:
- https://www.aclweb.org/anthology/2020.osact-1.9.pdf
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