Abstract
The use of abusive language on social media platforms is a prevalent issue that requires effective detection. Researchers actively engage in abusive language detection and sentiment analysis on social media platforms. However, most of the studies are in English. Hence, there is a need to develop models for low-resource languages. Further, the multimodal content in social media platforms is expanding rapidly. Our research aims to address this gap by developing a multimodal abusive language detection and performing sentiment analysis for Tamil and Malayalam, two under-resourced languages, based on the shared task Multimodal Abusive Language Detection and Sentiment Analysis in Dravidian Languages: DravidianLangTech@RANLP 2023”. In our study, we conduct extensive experiments utilizing multiple deep-learning models to detect abusive language in Tamil and perform sentiment analysis in Tamil and Malayalam. For feature extraction, we use the mBERT transformer-based model for texts, the ViT model for images and MFCC for audio. In the abusive language detection task, we achieved a weighted average F1 score of 0.5786, securing the first rank in this task. For sentiment analysis, we achieved a weighted average F1 score of 0.357 for Tamil and 0.233 for Malayalam, ranking first in this task.- Anthology ID:
- 2023.dravidianlangtech-1.31
- Volume:
- Proceedings of the Third Workshop on Speech and Language Technologies for Dravidian Languages
- Month:
- September
- Year:
- 2023
- Address:
- Varna, Bulgaria
- Editors:
- Bharathi R. Chakravarthi, Ruba Priyadharshini, Anand Kumar M, Sajeetha Thavareesan, Elizabeth Sherly
- Venues:
- DravidianLangTech | WS
- SIG:
- Publisher:
- INCOMA Ltd., Shoumen, Bulgaria
- Note:
- Pages:
- 217–224
- Language:
- URL:
- https://aclanthology.org/2023.dravidianlangtech-1.31
- DOI:
- Cite (ACL):
- Shubhankar Barman and Mithun Das. 2023. hate-alert@DravidianLangTech: Multimodal Abusive Language Detection and Sentiment Analysis in Dravidian Languages. In Proceedings of the Third Workshop on Speech and Language Technologies for Dravidian Languages, pages 217–224, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
- Cite (Informal):
- hate-alert@DravidianLangTech: Multimodal Abusive Language Detection and Sentiment Analysis in Dravidian Languages (Barman & Das, DravidianLangTech-WS 2023)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.dravidianlangtech-1.31.pdf