Health Misinformation in Social Networks: A Survey of Information Technology Approaches

Vasiliki Papanikou, Panagiotis Papadakos (), Theodora Karamanidou, Thanos G. Stavropoulos, Evaggelia Pitoura and Panayiotis Tsaparas
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Vasiliki Papanikou: Computer Science and Engineering Department (CSE), University of Ioannina (UOI), 45110 Ioannina, Greece
Panagiotis Papadakos: Computer Science and Engineering Department (CSE), University of Ioannina (UOI), 45110 Ioannina, Greece
Theodora Karamanidou: Center for Digital Innovation (CDI), Pfizer, 55535 Thessaloniki, Greece
Thanos G. Stavropoulos: Center for Digital Innovation (CDI), Pfizer, 55535 Thessaloniki, Greece
Evaggelia Pitoura: Computer Science and Engineering Department (CSE), University of Ioannina (UOI), 45110 Ioannina, Greece
Panayiotis Tsaparas: Computer Science and Engineering Department (CSE), University of Ioannina (UOI), 45110 Ioannina, Greece

Future Internet, 2025, vol. 17, issue 3, 1-50

Abstract: In this paper, we present a comprehensive survey on the pervasive issue of medical misinformation in social networks from the perspective of information technology. The survey aims at providing a systematic review of related research and helping researchers and practitioners navigate through this fast-changing field. Research on misinformation spans multiple disciplines, but technical surveys rarely focus on the medical domain. Existing medical misinformation surveys provide broad insights for various stakeholders but lack a deep dive into computational methods. This survey fills that gap by examining how fact-checking and fake news detection techniques are adapted to the medical field from a computer engineering perspective. Specifically, we first present manual and automatic approaches for fact-checking, along with publicly available fact-checking tools. We then explore fake news detection methods, using content, propagation features, or source features, as well as mitigation approaches for countering the spread of misinformation. We also provide a detailed list of several datasets on health misinformation. While this survey primarily serves researchers and technology experts, it can also provide valuable insights for policymakers working to combat health misinformation. We conclude the survey with a discussion on the open challenges and future research directions in the battle against health misinformation.

Keywords: misinformation; fake news; fact-checking; medical domain; COVID-19; information technology approaches; survey (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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