Abstract
Propaganda is information or ideas that an organized group or government spreads to influence peopleś opinions, especially by not giving all the facts or secretly emphasizing only one way of looking at the points. The ability to automatically detect propaganda-related linguistic signs is a challenging task that researchers in the NLP community have recently started to address. This paper presents the participation of our team AraBEM in the propaganda detection shared task on Arabic tweets. Our system utilized a pre-trained BERT model to perform multi-class binary classification. It attained the best score at 0.602 micro-f1, ranking third on subtask-1, which identifies the propaganda techniques as a multilabel classification problem with a baseline of 0.079.- Anthology ID:
- 2022.wanlp-1.62
- Volume:
- Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Houda Bouamor, Hend Al-Khalifa, Kareem Darwish, Owen Rambow, Fethi Bougares, Ahmed Abdelali, Nadi Tomeh, Salam Khalifa, Wajdi Zaghouani
- Venue:
- WANLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 524–528
- Language:
- URL:
- https://aclanthology.org/2022.wanlp-1.62
- DOI:
- 10.18653/v1/2022.wanlp-1.62
- Cite (ACL):
- Eshrag Ali Refaee, Basem Ahmed, and Motaz Saad. 2022. AraBEM at WANLP 2022 Shared Task: Propaganda Detection in Arabic Tweets. In Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP), pages 524–528, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- AraBEM at WANLP 2022 Shared Task: Propaganda Detection in Arabic Tweets (Refaee et al., WANLP 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.wanlp-1.62.pdf