Abstract
This research presents our team KEIS@JUST participation at SemEval-2020 Task 12 which represents shared task on multilingual offensive language. We participated in all the provided languages for all subtasks except sub-task-A for the English language. Two main approaches have been developed the first is performed to tackle both languages Arabic and English, a weighted ensemble consists of Bi-GRU and CNN followed by Gaussian noise and global pooling layer multiplied by weights to improve the overall performance. The second is performed for other languages, a transfer learning from BERT beside the recurrent neural networks such as Bi-LSTM and Bi-GRU followed by a global average pooling layer. Word embedding and contextual embedding have been used as features, moreover, data augmentation has been used only for the Arabic language.- Anthology ID:
- 2020.semeval-1.269
- 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:
- 2035–2044
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.269
- DOI:
- 10.18653/v1/2020.semeval-1.269
- Cite (ACL):
- Saja Tawalbeh, Mahmoud Hammad, and Mohammad AL-Smadi. 2020. KEIS@JUST at SemEval-2020 Task 12: Identifying Multilingual Offensive Tweets Using Weighted Ensemble and Fine-Tuned BERT. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 2035–2044, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- KEIS@JUST at SemEval-2020 Task 12: Identifying Multilingual Offensive Tweets Using Weighted Ensemble and Fine-Tuned BERT (Tawalbeh et al., SemEval 2020)
- PDF:
- https://preview.aclanthology.org/landing_page/2020.semeval-1.269.pdf
- Data
- OLID