Health Misinformation in Social Networks: A Survey of IT Approaches

• Main Authors: Papanikou, Vasiliki, Papadakos, Panagiotis, Karamanidou, Theodora, Stavropoulos, Thanos G, Pitoura, Evaggelia, Tsaparas, Panayiotis
• Format: Journal Article
• Language: English
• Published: 24-10-2024
• Subjects: Computer Science - Artificial Intelligence; Computer Science - Computation and Language; Computer Science - Learning; Computer Science - Social and Information Networks
• DOI: 10.48550/arxiv.2410.18670

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. Specifically, we first present manual and automatic
approaches for fact-checking. 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 and of publicly
available tools. We conclude the survey with a discussion on the open
challenges and future research directions in the battle against health
misinformation.