@inproceedings{sathvik-etal-2025-detection,
title = "Detection of Religious Hate Speech During Elections in {K}arnataka",
author = "Sathvik, Msvpj and
Sonani, Raj and
Potla, Ravi Teja",
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-1.97/",
doi = "10.18653/v1/2025.dravidianlangtech-1.97",
pages = "562--566",
ISBN = "979-8-89176-228-2",
abstract = "We propose a novel dataset for detecting religious hate speech in the context of elections in Karnataka, with a particular focus on Kannada and Kannada-English code-mixed text. The data was collected during the Karnataka state elections and includes 3,000 labeled samples that reflect various forms of online discourse related to religion. This dataset aims to address the growing concern of religious intolerance and hate speech during election periods, it{'}s a dataset of multilingual, code-mixed language. To evaluate the effectiveness of this dataset, we benchmarked it using the latest state-of-the-art algorithms. We achieved accuracy of 78.61{\%}."
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%0 Conference Proceedings
%T Detection of Religious Hate Speech During Elections in Karnataka
%A Sathvik, Msvpj
%A Sonani, Raj
%A Potla, Ravi Teja
%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 sathvik-etal-2025-detection
%X We propose a novel dataset for detecting religious hate speech in the context of elections in Karnataka, with a particular focus on Kannada and Kannada-English code-mixed text. The data was collected during the Karnataka state elections and includes 3,000 labeled samples that reflect various forms of online discourse related to religion. This dataset aims to address the growing concern of religious intolerance and hate speech during election periods, it’s a dataset of multilingual, code-mixed language. To evaluate the effectiveness of this dataset, we benchmarked it using the latest state-of-the-art algorithms. We achieved accuracy of 78.61%.
%R 10.18653/v1/2025.dravidianlangtech-1.97
%U https://aclanthology.org/2025.dravidianlangtech-1.97/
%U https://doi.org/10.18653/v1/2025.dravidianlangtech-1.97
%P 562-566
Markdown (Informal)
[Detection of Religious Hate Speech During Elections in Karnataka](https://aclanthology.org/2025.dravidianlangtech-1.97/) (Sathvik et al., DravidianLangTech 2025)
ACL
- Msvpj Sathvik, Raj Sonani, and Ravi Teja Potla. 2025. Detection of Religious Hate Speech During Elections in Karnataka. In Proceedings of the Fifth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, pages 562–566, Acoma, The Albuquerque Convention Center, Albuquerque, New Mexico. Association for Computational Linguistics.