Abstract
This paper presents our strategy to tackle the EACL WANLP-2021 Shared Task 2: Sarcasm and Sentiment Detection. One of the subtasks aims at developing a system that identifies whether a given Arabic tweet is sarcastic in nature or not, while the other aims to identify the sentiment of the Arabic tweet. We approach the task in two steps. The first step involves pre processing the provided dataset by performing insertions, deletions and segmentation operations on various parts of the text. The second step involves experimenting with multiple variants of two transformer based models, AraELECTRA and AraBERT. Our final approach was ranked seventh and fourth in the Sarcasm and Sentiment Detection subtasks respectively.- Anthology ID:
- 2021.wanlp-1.53
- Volume:
- Proceedings of the Sixth Arabic Natural Language Processing Workshop
- Month:
- April
- Year:
- 2021
- Address:
- Kyiv, Ukraine (Virtual)
- Editors:
- Nizar Habash, Houda Bouamor, Hazem Hajj, Walid Magdy, Wajdi Zaghouani, Fethi Bougares, Nadi Tomeh, Ibrahim Abu Farha, Samia Touileb
- Venue:
- WANLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 395–400
- Language:
- URL:
- https://aclanthology.org/2021.wanlp-1.53
- DOI:
- Cite (ACL):
- Anshul Wadhawan. 2021. AraBERT and Farasa Segmentation Based Approach For Sarcasm and Sentiment Detection in Arabic Tweets. In Proceedings of the Sixth Arabic Natural Language Processing Workshop, pages 395–400, Kyiv, Ukraine (Virtual). Association for Computational Linguistics.
- Cite (Informal):
- AraBERT and Farasa Segmentation Based Approach For Sarcasm and Sentiment Detection in Arabic Tweets (Wadhawan, WANLP 2021)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2021.wanlp-1.53.pdf
- Data
- ArSarcasm-v2