Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims

• URL: http://arxiv.org/abs/2204.12294v1
• Date: Tue, 26 Apr 2022 13:18:27 GMT
• Title: Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims
• Authors: Ivan Srba, Branislav Pecher, Matus Tomlein, Robert Moro, Elena Stefancova, Jakub Simko, Maria Bielikova
• Abstract summary: We publish a feature-rich dataset of 317k medical news articles/blogs and 3.5k fact-checked claims. It also contains 573 manually and more than 51k automatically labelled mappings between claims and articles. The dataset enables a number of additional tasks related to medical misinformation, such as misinformation characterisation studies or studies of misinformation diffusion between sources.
• Score: 0.6927055673104934
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: False information has a significant negative influence on individuals as well as on the whole society. Especially in the current COVID-19 era, we witness an unprecedented growth of medical misinformation. To help tackle this problem with machine learning approaches, we are publishing a feature-rich dataset of approx. 317k medical news articles/blogs and 3.5k fact-checked claims. It also contains 573 manually and more than 51k automatically labelled mappings between claims and articles. Mappings consist of claim presence, i.e., whether a claim is contained in a given article, and article stance towards the claim. We provide several baselines for these two tasks and evaluate them on the manually labelled part of the dataset. The dataset enables a number of additional tasks related to medical misinformation, such as misinformation characterisation studies or studies of misinformation diffusion between sources.

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