@inproceedings{shanmugavadivel-etal-2025-blueray,
title = "{B}lue{R}ay@{D}ravidian{L}ang{T}ech-2025: Fake News Detection in {D}ravidian Languages",
author = "Shanmugavadivel, Kogilavani and
Subramanian, Malliga and
M, Aiswarya and
T, Aruna and
S, Jeevaananth",
editor = "Chakravarthi, Bharathi Raja and
Priyadharshini, Ruba and
Madasamy, Anand Kumar and
Thavareesan, Sajeetha and
Sherly, Elizabeth and
Rajiakodi, Saranya and
Palani, Balasubramanian and
Subramanian, Malliga and
Cn, Subalalitha and
Chinnappa, Dhivya",
booktitle = "Proceedings of the Fifth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages",
month = may,
year = "2025",
address = "Acoma, The Albuquerque Convention Center, Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.dravidianlangtech-1.39/",
doi = "10.18653/v1/2025.dravidianlangtech-1.39",
pages = "226--231",
ISBN = "979-8-89176-228-2",
abstract = "The rise of fake news presents significant issues, particularly for underrepresented lan guages. This study tackles fake news identification in Dravidian languages with two subtasks: binary classification of YouTube comments and multi-class classification of Malayalam news into five groups. Text preprocessing, vectorization, and transformer-based embeddings are all part of the methodology, including baseline comparisons utilizing classic machine learning, deep learning, and transfer learning models. In Task 1, our solution placed 17th, displaying acceptable binary classification per formance. In Task 2, we finished eighth place by effectively identifying nuanced categories of Malayalam news, demonstrating the efficacy of transformer-based models."
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%0 Conference Proceedings
%T BlueRay@DravidianLangTech-2025: Fake News Detection in Dravidian Languages
%A Shanmugavadivel, Kogilavani
%A Subramanian, Malliga
%A M, Aiswarya
%A T, Aruna
%A S, Jeevaananth
%Y Chakravarthi, Bharathi Raja
%Y Priyadharshini, Ruba
%Y Madasamy, Anand Kumar
%Y Thavareesan, Sajeetha
%Y Sherly, Elizabeth
%Y Rajiakodi, Saranya
%Y Palani, Balasubramanian
%Y Subramanian, Malliga
%Y Cn, Subalalitha
%Y Chinnappa, Dhivya
%S Proceedings of the Fifth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages
%D 2025
%8 May
%I Association for Computational Linguistics
%C Acoma, The Albuquerque Convention Center, Albuquerque, New Mexico
%@ 979-8-89176-228-2
%F shanmugavadivel-etal-2025-blueray
%X The rise of fake news presents significant issues, particularly for underrepresented lan guages. This study tackles fake news identification in Dravidian languages with two subtasks: binary classification of YouTube comments and multi-class classification of Malayalam news into five groups. Text preprocessing, vectorization, and transformer-based embeddings are all part of the methodology, including baseline comparisons utilizing classic machine learning, deep learning, and transfer learning models. In Task 1, our solution placed 17th, displaying acceptable binary classification per formance. In Task 2, we finished eighth place by effectively identifying nuanced categories of Malayalam news, demonstrating the efficacy of transformer-based models.
%R 10.18653/v1/2025.dravidianlangtech-1.39
%U https://aclanthology.org/2025.dravidianlangtech-1.39/
%U https://doi.org/10.18653/v1/2025.dravidianlangtech-1.39
%P 226-231
Markdown (Informal)
[BlueRay@DravidianLangTech-2025: Fake News Detection in Dravidian Languages](https://aclanthology.org/2025.dravidianlangtech-1.39/) (Shanmugavadivel et al., DravidianLangTech 2025)
ACL
- Kogilavani Shanmugavadivel, Malliga Subramanian, Aiswarya M, Aruna T, and Jeevaananth S. 2025. BlueRay@DravidianLangTech-2025: Fake News Detection in Dravidian Languages. In Proceedings of the Fifth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, pages 226–231, Acoma, The Albuquerque Convention Center, Albuquerque, New Mexico. Association for Computational Linguistics.