@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://preview.aclanthology.org/moar-dois/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{\%}."
}