Empowering COVID-19 Fact-Checking with Extended Knowledge Graphs

Paolo Mengoni*, Jinyu Yang

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

1 Citation (Scopus)


During the COVID-19 outbreak, fake news regarding the disease have spread at an increasing rate. Let’s think, for instance, to face masks wearing related news or various home-made treatments to cure the disease. To contrast this phenomenon, the fact-checking community has intensified its efforts by producing a large number of fact-checking reports. In this work, we focus on empowering knowledge-based approaches for misinformation identification with previous knowledge gathered from existing fact-checking reports. Very few works in literature have exploited the information regarding claims that have been already fact-checked. The main idea that we explore in this work is to exploit the detailed information in the COVID-19 fact check reports in order to create an extended Knowledge Graph. By analysing the graph information about the already checked claims, we can verify newly coming content more effectively. Another gap that we aim to fill is the temporal representation of the facts stored in the knowledge graph. At the best of our knowledge, this is the first attempt to associate the temporal validity to the KG relations. This additional information can be used to further enhance the validation of claims.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2022 Workshops
Subtitle of host publicationMalaga, Spain, July 4–7, 2022, Proceedings, Part I
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Ana Maria A.C. Rocha, Chiara Garau
PublisherSpringer Cham
Number of pages13
ISBN (Electronic)9783031105364
ISBN (Print)9783031105357
Publication statusPublished - 23 Jul 2022
Event22nd International Conference on Computational Science and Its Applications , ICCSA 2022 - Malaga, Spain
Duration: 4 Jul 20227 Jul 2022
https://link.springer.com/book/10.1007/978-3-031-10536-4 (Conference proceedings)

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameICCSA: International Conference on Computational Science and Its Applications


Conference22nd International Conference on Computational Science and Its Applications , ICCSA 2022
Internet address

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Fact checking
  • Knowledge graphs
  • Natural Language Processing


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