Subalalitha Chinnaudayar Navaneethakrishnan
2025
Overview of the Shared Task on Detecting Racial Hoaxes in Code-Mixed Hindi-English Social Media Data
Bharathi Raja Chakravarthi
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Prasanna Kumar Kumaresan
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Shanu Dhawale
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Saranya Rajiakodi
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Sajeetha Thavareesan
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Subalalitha Chinnaudayar Navaneethakrishnan
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Thenmozhi Durairaj
Proceedings of the 5th Conference on Language, Data and Knowledge: Fifth Workshop on Language Technology for Equality, Diversity, Inclusion
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.