Abstract
We present three methods developed for the Shared Task on Sarcasm and Sentiment Detection in Arabic. We present a baseline that uses character n-gram features. We also propose two more sophisticated methods: a recurrent neural network with a word level representation and an ensemble classifier relying on word and character-level features. We chose to present results from an ensemble classifier but it was not very successful as compared to the best systems : 22th/37 on sarcasm detection and 15th/22 on sentiment detection. It finally appeared that our baseline could have been improved and beat those results.- Anthology ID:
- 2021.wanlp-1.41
- Volume:
- Proceedings of the Sixth Arabic Natural Language Processing Workshop
- Month:
- April
- Year:
- 2021
- Address:
- Kyiv, Ukraine (Virtual)
- Venue:
- WANLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 329–333
- Language:
- URL:
- https://aclanthology.org/2021.wanlp-1.41
- DOI:
- Cite (ACL):
- Dhaou Ghoul and Gaël Lejeune. 2021. Sarcasm and Sentiment Detection in Arabic: investigating the interest of character-level features. In Proceedings of the Sixth Arabic Natural Language Processing Workshop, pages 329–333, Kyiv, Ukraine (Virtual). Association for Computational Linguistics.
- Cite (Informal):
- Sarcasm and Sentiment Detection in Arabic: investigating the interest of character-level features (Ghoul & Lejeune, WANLP 2021)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2021.wanlp-1.41.pdf