Abstract
This paper presents our systems and findings for SemEval-2023 Task 12: AfriSenti-SemEval: Sentiment Analysis for Low-resource African Languages. The main objective of this task was to determine the polarity of a tweet (positive, negative, or neutral). Our submitted models (highest rank is 1 and lowest rank is 21 depending on the target Track) consist of various Transformer-based approaches.- Anthology ID:
- 2023.semeval-1.28
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 199–204
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.28
- DOI:
- 10.18653/v1/2023.semeval-1.28
- Cite (ACL):
- Abdessamad Benlahbib and Achraf Boumhidi. 2023. NLP-LISAC at SemEval-2023 Task 12: Sentiment Analysis for Tweets expressed in African languages via Transformer-based Models. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 199–204, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- NLP-LISAC at SemEval-2023 Task 12: Sentiment Analysis for Tweets expressed in African languages via Transformer-based Models (Benlahbib & Boumhidi, SemEval 2023)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2023.semeval-1.28.pdf