Proceedings:
Vol. 15 (2021): Fifteenth International AAAI Conference on Web and Social Media
Volume
Issue:
Vol. 15 (2021): Fifteenth International AAAI Conference on Web and Social Media
Track:
Dataset Papers
Downloads:
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).
DOI:
10.1609/icwsm.v15i1.18126
ICWSM
Vol. 15 (2021): Fifteenth International AAAI Conference on Web and Social Media