@inproceedings{a-aghila-2025-dltcnitpy,
title = "{DLTCNITPY}@{D}ravidian{L}ang{T}ech 2025 Abusive Code-mixed Text Detection System Targeting Women for {T}amil and {M}alayalam Languages using Deep Learning Technique",
author = "A, Habiba and
G, Aghila",
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-1.98/",
doi = "10.18653/v1/2025.dravidianlangtech-1.98",
pages = "567--572",
ISBN = "979-8-89176-228-2",
abstract = "The growing use of social communication platforms has seen women facing higher degrees of online violence than ever before. This paper presents how a deep learning abuse detection system can be applied to inappropriate text directed at women on social media. Because of the diversity of languages and the casual nature of online communication, coupled with the cultural diversity around the world, the detection of such content is often severely lacking. This research utilized Long Short-Term Memory (LSTM) for abuse text detection in Malayalam and Tamil languages. This modeldelivers 0.75, a high F1 score for Malayalam, and for Tamil, 0.72, achieving the desired balance of identifying abuse and non-abusive content and achieving high-performance rates. The designed model, based on the dataset provided in DravidianLangTech@NAACL2025 (shared task) comprising code-mixed abusive and nonabusive social media posts in Malayalam and Tamil, showcases a high propensity for detecting accuracy and indicates the likely success of deep learning-based models for abuse textdetection in resource-constrained languages."
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%0 Conference Proceedings
%T DLTCNITPY@DravidianLangTech 2025 Abusive Code-mixed Text Detection System Targeting Women for Tamil and Malayalam Languages using Deep Learning Technique
%A A, Habiba
%A G, Aghila
%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 a-aghila-2025-dltcnitpy
%X The growing use of social communication platforms has seen women facing higher degrees of online violence than ever before. This paper presents how a deep learning abuse detection system can be applied to inappropriate text directed at women on social media. Because of the diversity of languages and the casual nature of online communication, coupled with the cultural diversity around the world, the detection of such content is often severely lacking. This research utilized Long Short-Term Memory (LSTM) for abuse text detection in Malayalam and Tamil languages. This modeldelivers 0.75, a high F1 score for Malayalam, and for Tamil, 0.72, achieving the desired balance of identifying abuse and non-abusive content and achieving high-performance rates. The designed model, based on the dataset provided in DravidianLangTech@NAACL2025 (shared task) comprising code-mixed abusive and nonabusive social media posts in Malayalam and Tamil, showcases a high propensity for detecting accuracy and indicates the likely success of deep learning-based models for abuse textdetection in resource-constrained languages.
%R 10.18653/v1/2025.dravidianlangtech-1.98
%U https://aclanthology.org/2025.dravidianlangtech-1.98/
%U https://doi.org/10.18653/v1/2025.dravidianlangtech-1.98
%P 567-572
Markdown (Informal)
[DLTCNITPY@DravidianLangTech 2025 Abusive Code-mixed Text Detection System Targeting Women for Tamil and Malayalam Languages using Deep Learning Technique](https://aclanthology.org/2025.dravidianlangtech-1.98/) (A & G, DravidianLangTech 2025)
ACL