Publication Type : Book Chapter
Publisher : Springer Nature Switzerland
Source : Communications in Computer and Information Science
Url : https://doi.org/10.1007/978-3-032-05855-3_13
Keywords : Fact check, Tamil, Dataset, Social Media, Fake news, Multimodal
Campus : Coimbatore
School : School of Artificial Intelligence
Year : 2025
Abstract : The creation and spread of misinformation through social media in regional languages is an escalating problem. There is a need to scrutinize these fabricated multimedia contents, especially in a low-resource language context. Current limitations in fake news detection research underscore the need for a comprehensive multimodal dataset in the Tamil language. This study proposes a multimodal dataset for fake news classification in Tamil, comprising 7,934 data samples across three modalities: text, image, and speech, curated from various Tamil fact-check websites. We develop the first Tamil speech corpus for fake news classification, encompassing 884 min of audio derived from fact-checked news articles, facilitating multimodal analysis. Additionally, we have gathered a substantial collection of 7934 images from fact-check Tamil news articles to explore the relationship between visual and textual data in the …
Cite this Research Publication : Meclin A. Francis, Ayswarya R. Kurup, B. Premjith, Bharathi Raja Chakravarthi, Saranya Rajiakodi, TamilFacts: A Comprehensive Multimodal Dataset of Fact-Checked Social Media Content in Tamil Language, Communications in Computer and Information Science, Springer Nature Switzerland, 2025, https://doi.org/10.1007/978-3-032-05855-3_13