Abstract
We describe our submitted system to the SemEval 2020. We tackled Task 12 entitled “Multilingual Offensive Language Identification in Social Media”, specifically subtask 4A-Arabic. We propose three Arabic offensive language identification models: Tw-StAR, BERT and BERT+BiLSTM. Two Arabic abusive/hate datasets were added to the training dataset: L-HSAB and T-HSAB. The final submission was chosen based on the best performances which was achieved by the BERT+BiLSTM model.- Anthology ID:
- 2020.semeval-1.260
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Editors:
- Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 1978–1982
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.260
- DOI:
- 10.18653/v1/2020.semeval-1.260
- Cite (ACL):
- Abir Messaoudi, Hatem Haddad, and Moez Ben Haj Hmida. 2020. iCompass at SemEval-2020 Task 12: From a Syntax-ignorant N-gram Embeddings Model to a Deep Bidirectional Language Model. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1978–1982, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- iCompass at SemEval-2020 Task 12: From a Syntax-ignorant N-gram Embeddings Model to a Deep Bidirectional Language Model (Messaoudi et al., SemEval 2020)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2020.semeval-1.260.pdf