NLP-LISAC at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation
Abdessamad Benlahbib, Hamza Alami, Achraf Boumhidi, Omar Benslimane
Abstract
This paper presents our system and findings for SemEval 2023 Task 9 Tweet Intimacy Analysis. The main objective of this task was to predict the intimacy of tweets in 10 languages. Our submitted model (ranked 28/45) consists of a transformer-based approach with data augmentation via machine translation.- Anthology ID:
- 2023.semeval-1.16
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 121–124
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.16
- DOI:
- 10.18653/v1/2023.semeval-1.16
- Cite (ACL):
- Abdessamad Benlahbib, Hamza Alami, Achraf Boumhidi, and Omar Benslimane. 2023. NLP-LISAC at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 121–124, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- NLP-LISAC at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation (Benlahbib et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2023.semeval-1.16.pdf