Check Mate: Prioritizing User Generated Multi-Media Content for Fact-Checking


  • Tarunima Prabhakar Tattle Civic Technologies
  • Anushree Gupta Tattle Civic Technologies
  • Kruttika Nadig Tattle Civic Technologies
  • Denny George Tattle Civic Technologies



Credibility of online content, New social media applications; interfaces; interaction techniques, Qualitative and quantitative studies of social media, Trust; reputation; recommendation systems


Volume of content and misinformation on social media is rapidly increasing. There is a need for systems that can support fact checkers by prioritizing content that needs to be fact checked. Prior research on prioritizing content for fact-checking has focused on news media articles, predominantly in English language. Increasingly, misinformation is found in user-generated content. In this paper we present a novel dataset that can be used to prioritize check-worthy posts from multi-media content in Hindi. It is unique in its 1) focus on user generated content, 2) language and 3) accommodation of multi-modality in social media posts. In addition, we also provide metadata for each post such as number of shares and likes of the post on ShareChat, a popular Indian social media platform, that allows for correlative analysis around virality and misinformation. The data is accessible on Zenodo ( under Creative Commons Attribution License (CC BY 4.0).




How to Cite

Prabhakar, T., Gupta, A., Nadig, K., & George, D. (2021). Check Mate: Prioritizing User Generated Multi-Media Content for Fact-Checking. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 1025-1033.