“The coronavirus is a bioweapon”: classifying coronavirus stories on fact-checking sites

Lynnette Hui Xian Ng () and Kathleen M. Carley ()
Additional contact information
Lynnette Hui Xian Ng: Carnegie Mellon University
Kathleen M. Carley: Carnegie Mellon University

Computational and Mathematical Organization Theory, 2021, vol. 27, issue 2, No 4, 179-194

Abstract: Abstract The 2020 coronavirus pandemic has heightened the need to flag coronavirus-related misinformation, and fact-checking groups have taken to verifying misinformation on the Internet. We explore stories reported by fact-checking groups PolitiFact, Poynter and Snopes from January to June 2020. We characterise these stories into six clusters, then analyse temporal trends of story validity and the level of agreement across sites. The sites present the same stories 78% of the time, with the highest agreement between Poynter and PolitiFact. We further break down the story clusters into more granular story types by proposing a unique automated method, which can be used to classify diverse story sources in both fact-checked stories and tweets. Our results show story type classification performs best when trained on the same medium, with contextualised BERT vector representations outperforming a Bag-Of-Words classifier.

Keywords: Coronavirus; Fact checking; Misinformation; Social cybersecurity; Text classification (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10588-021-09329-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:comaot:v:27:y:2021:i:2:d:10.1007_s10588-021-09329-w

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10588

DOI: 10.1007/s10588-021-09329-w

Access Statistics for this article

Computational and Mathematical Organization Theory is currently edited by Terrill Frantz and Kathleen Carley

More articles in Computational and Mathematical Organization Theory from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().