Abstract
The proliferation of health misinformation in recent years has prompted the development of various methods for detecting and combatting this issue. This review aims to provide an overview of the implementation strategies and characteristics of publicly available datasets that can be used for health misinformation detection. Since 2020, a large number of such datasets have emerged, half of which are focused on COVID-19. Most of the datasets are based on fact-checkable websites, while only a few are annotated by experts. Furthermore, some datasets provide additional information such as social engagement and explanations, which can be utilized to study the spread of misinformation. Overall, these datasets offer a valuable resource for researchers working to combat the spread and consequences of health misinformation.
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