CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweets

Isabelle Mohr, Amelie Wührl, Roman Klinger


Abstract
During the first two years of the COVID-19 pandemic, large volumes of biomedical information concerning this new disease have been published on social media. Some of this information can pose a real danger, particularly when false information is shared, for instance recommendations how to treat diseases without professional medical advice. Therefore, automatic fact-checking resources and systems developed specifically for medical domain are crucial. While existing fact-checking resources cover COVID-19 related information in news or quantify the amount of misinformation in tweets, there is no dataset providing fact-checked COVID-19 related Twitter posts with detailed annotations for biomedical entities, relations and relevant evidence. We contribute CoVERT, a fact-checked corpus of tweets with a focus on the domain of biomedicine and COVID-19 related (mis)information. The corpus consists of 300 tweets, each annotated with named entities and relations. We employ a novel crowdsourcing methodology to annotate all tweets with fact-checking labels and supporting evidence, which crowdworkers search for online. This methodology results in substantial inter-annotator agreement. Furthermore, we use the retrieved evidence extracts as part of a fact-checking pipeline, finding that the real-world evidence is more useful than the knowledge directly available in pretrained language models.
Anthology ID:
2022.lrec-1.26
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
244–257
Language:
URL:
https://aclanthology.org/2022.lrec-1.26
DOI:
Bibkey:
Cite (ACL):
Isabelle Mohr, Amelie Wührl, and Roman Klinger. 2022. CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweets. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 244–257, Marseille, France. European Language Resources Association.
Cite (Informal):
CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweets (Mohr et al., LREC 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.lrec-1.26.pdf
Data
CoVERTBioLAMA