Check Mate: Prioritizing User Generated Multi-Media Content for Fact-Checking
Abstract
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 (https://zenodo.org/record/4032629) under Creative Commons Attribution License (CC BY 4.0).
Cite
@article{arxiv.2010.13387,
title = {Check Mate: Prioritizing User Generated Multi-Media Content for Fact-Checking},
author = {Tarunima Prabhakar and Anushree Gupta and Kruttika Nadig and Denny George},
journal= {arXiv preprint arXiv:2010.13387},
year = {2021}
}
Comments
8 pages, 13 figures, 2 tables