@inproceedings{chakravarthi-etal-2025-overview-shared,
title = "Overview of the Shared Task on Detecting Racial Hoaxes in Code-Mixed {H}indi-{E}nglish Social Media Data",
author = "Chakravarthi, Bharathi Raja and
Kumaresan, Prasanna Kumar and
Dhawale, Shanu and
Rajiakodi, Saranya and
Thavareesan, Sajeetha and
Navaneethakrishnan, Subalalitha Chinnaudayar and
Durairaj, Thenmozhi",
editor = "Gkirtzou, Katerina and
{\v{Z}}itnik, Slavko and
Gracia, Jorge and
Gromann, Dagmar and
di Buono, Maria Pia and
Monti, Johanna and
Ionov, Maxim",
booktitle = "Proceedings of the 5th Conference on Language, Data and Knowledge: Fifth Workshop on Language Technology for Equality, Diversity, Inclusion",
month = sep,
year = "2025",
address = "Naples, Italy",
publisher = "Unior Press",
url = "https://aclanthology.org/2025.ltedi-1.35/",
pages = "222--228",
ISBN = "978-88-6719-334-9",
abstract = "The widespread use of social media has made it easier for false information to proliferate, particularly racially motivated hoaxes that can encourage violence and hatred. Such content is frequently shared in code-mixed languages in multilingual nations like India, which presents special difficulties for automated detection systems because of the casual language, erratic grammar, and rich cultural background. The shared task on detecting racial hoaxes in code mixed social media data aims to identify the racial hoaxes in Hindi-English data. It is a binary classification task with more than 5,000 labeled instances. A total of 11 teams participated in the task, and the results are evaluated using the macro-F1 score. The team that employed XLM-RoBERTa secured the first position in the task."
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%0 Conference Proceedings
%T Overview of the Shared Task on Detecting Racial Hoaxes in Code-Mixed Hindi-English Social Media Data
%A Chakravarthi, Bharathi Raja
%A Kumaresan, Prasanna Kumar
%A Dhawale, Shanu
%A Rajiakodi, Saranya
%A Thavareesan, Sajeetha
%A Navaneethakrishnan, Subalalitha Chinnaudayar
%A Durairaj, Thenmozhi
%Y Gkirtzou, Katerina
%Y Žitnik, Slavko
%Y Gracia, Jorge
%Y Gromann, Dagmar
%Y di Buono, Maria Pia
%Y Monti, Johanna
%Y Ionov, Maxim
%S Proceedings of the 5th Conference on Language, Data and Knowledge: Fifth Workshop on Language Technology for Equality, Diversity, Inclusion
%D 2025
%8 September
%I Unior Press
%C Naples, Italy
%@ 978-88-6719-334-9
%F chakravarthi-etal-2025-overview-shared
%X The widespread use of social media has made it easier for false information to proliferate, particularly racially motivated hoaxes that can encourage violence and hatred. Such content is frequently shared in code-mixed languages in multilingual nations like India, which presents special difficulties for automated detection systems because of the casual language, erratic grammar, and rich cultural background. The shared task on detecting racial hoaxes in code mixed social media data aims to identify the racial hoaxes in Hindi-English data. It is a binary classification task with more than 5,000 labeled instances. A total of 11 teams participated in the task, and the results are evaluated using the macro-F1 score. The team that employed XLM-RoBERTa secured the first position in the task.
%U https://aclanthology.org/2025.ltedi-1.35/
%P 222-228
Markdown (Informal)
[Overview of the Shared Task on Detecting Racial Hoaxes in Code-Mixed Hindi-English Social Media Data](https://aclanthology.org/2025.ltedi-1.35/) (Chakravarthi et al., LTEDI 2025)
ACL
- Bharathi Raja Chakravarthi, Prasanna Kumar Kumaresan, Shanu Dhawale, Saranya Rajiakodi, Sajeetha Thavareesan, Subalalitha Chinnaudayar Navaneethakrishnan, and Thenmozhi Durairaj. 2025. Overview of the Shared Task on Detecting Racial Hoaxes in Code-Mixed Hindi-English Social Media Data. In Proceedings of the 5th Conference on Language, Data and Knowledge: Fifth Workshop on Language Technology for Equality, Diversity, Inclusion, pages 222–228, Naples, Italy. Unior Press.