Mithunja S


2024

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Overview of the Second Shared Task on Fake News Detection in Dravidian Languages: DravidianLangTech@EACL 2024
Malliga Subramanian | Bharathi Raja Chakravarthi | Kogilavani Shanmugavadivel | Santhiya Pandiyan | Prasanna Kumar Kumaresan | Balasubramanian Palani | Premjith B | Vanaja K | Mithunja S | Devika K | Hariprasath S.b | Haripriya B | Vigneshwar E
Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages

The rise of online social media has revolutionized communication, offering users a convenient way to share information and stay updated on current events. However, this surge in connectivity has also led to the proliferation of misinformation, commonly known as fake news. This misleading content, often disguised as legitimate news, poses a significant challenge as it can distort public perception and erode trust in reliable sources. This shared task consists of two subtasks such as task 1 and task 2. Task 1 aims to classify a given social media text into original or fake. The goal of the FakeDetect-Malayalam task2 is to encourage participants to develop effective models capable of accurately detecting and classifying fake news articles in the Malayalam language into different categories like False, Half True, Mostly False, Partly False, and Mostly True. For this shared task, 33 participants submitted their results.