A Survey on Automated Fact-Checking

University of Cambridge

Indexed incrossrefdatacitedoaj

Abstract

Abstract Fact-checking has become increasingly important due to the speed with which both information and misinformation can spread in the modern media ecosystem. Therefore, researchers have been exploring how fact-checking can be automated, using techniques based on natural language processing, machine learning, knowledge representation, and databases to automatically predict the veracity of claims. In this paper, we survey automated fact-checking stemming from natural language processing, and discuss its connections to related tasks and disciplines. In this process, we present an overview of existing datasets and models, aiming to unify the various definitions given and identify common concepts. Finally, we…

Citation impact

359
total citations
FWCI
124.83
Percentile
100%
References
267
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • Misinformation
  • Process (computing)
  • Representation (politics)
  • Data science
  • Artificial intelligence
  • Natural language
  • Machine learning
UN Sustainable Development Goals
  • Quality Education
No related works found for this paper.