CUETSentimentSillies@DravidianLangTech-EACL2024: Transformer-based Approach for Sentiment Analysis in Tamil and Tulu Code-Mixed Texts
Zannatul Tripty, Md. Nafis, Antu Chowdhury, Jawad Hossain, Shawly Ahsan, Avishek Das, Mohammed Moshiul Hoque
Abstract
Sentiment analysis (SA) on social media reviews has become a challenging research agenda in recent years due to the exponential growth of textual content. Although several effective solutions are available for SA in high-resourced languages, it is considered a critical problem for low-resourced languages. This work introduces an automatic system for analyzing sentiment in Tamil and Tulu code-mixed languages. Several ML (DT, RF, MNB), DL (CNN, BiLSTM, CNN+BiLSTM), and transformer-based models (Indic-BERT, XLM-RoBERTa, m-BERT) are investigated for SA tasks using Tamil and Tulu code-mixed textual data. Experimental outcomes reveal that the transformer-based models XLM-R and m-BERT surpassed others in performance for Tamil and Tulu, respectively. The proposed XLM-R and m-BERT models attained macro F1-scores of 0.258 (Tamil) and 0.468 (Tulu) on test datasets, securing the 2nd and 5th positions, respectively, in the shared task.- Anthology ID:
- 2024.dravidianlangtech-1.39
- Volume:
- Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages
- Month:
- March
- Year:
- 2024
- Address:
- St. Julian's, Malta
- Editors:
- Bharathi Raja Chakravarthi, Ruba Priyadharshini, Anand Kumar Madasamy, Sajeetha Thavareesan, Elizabeth Sherly, Rajeswari Nadarajan, Manikandan Ravikiran
- Venues:
- DravidianLangTech | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 234–239
- Language:
- URL:
- https://aclanthology.org/2024.dravidianlangtech-1.39
- DOI:
- Cite (ACL):
- Zannatul Tripty, Md. Nafis, Antu Chowdhury, Jawad Hossain, Shawly Ahsan, Avishek Das, and Mohammed Moshiul Hoque. 2024. CUETSentimentSillies@DravidianLangTech-EACL2024: Transformer-based Approach for Sentiment Analysis in Tamil and Tulu Code-Mixed Texts. In Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, pages 234–239, St. Julian's, Malta. Association for Computational Linguistics.
- Cite (Informal):
- CUETSentimentSillies@DravidianLangTech-EACL2024: Transformer-based Approach for Sentiment Analysis in Tamil and Tulu Code-Mixed Texts (Tripty et al., DravidianLangTech-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.dravidianlangtech-1.39.pdf