mlsanityData to 14 Oct 2026

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

arXiv 2204.12294 ↗First posted 26 Apr 2022cs.CL cs.CY cs.IRcited by 10

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Abstract (arXiv)

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.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 25 of its 53 references that are in the map. First posted on arXiv 26 Apr 2022.

Builds on

25 of 53 references.

References · 25

  1. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,375
  2. 2018Universal Sentence Encodercited by 489
  3. 2021A Survey on Automated Fact-Checkingcited by 378
  4. 2017Fake News Detection on Social Media: A Data Mining Perspectivecited by 336
  5. 2018FakeNewsNet: A Data Repository with News Content, Social Context and Spatialtemporal Information for Studying Fake News on Social Mediacited by 285
  6. 2021Automated Fact-Checking for Assisting Human Fact-Checkerscited by 144
  7. 2017Detection and Resolution of Rumours in Social Media: A Surveycited by 104
  8. 2020CoAID: COVID-19 Healthcare Misinformation Datasetcited by 84
  9. 2020That is a Known Lie: Detecting Previously Fact-Checked Claimscited by 82
  10. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  11. 2019Reasoning Over Semantic-Level Graph for Fact Checkingcited by 69
  12. 2020FakeCovid -- A Multilingual Cross-domain Fact Check News Dataset for COVID-19cited by 61
13 more
  1. 2017This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire than Real Newscited by 59
  2. 2021Automated Fact-Checking: A Surveycited by 55
  3. 2018A Retrospective Analysis of the Fake News Challenge Stance Detection Taskcited by 49
  4. 2018Integrating Stance Detection and Fact Checking in a Unified Corpuscited by 41
  5. 2020BanFakeNews: A Dataset for Detecting Fake News in Banglacited by 40
  6. 2019Combating Fake News: A Survey on Identification and Mitigation Techniquescited by 33
  7. 2019Weak Supervision for Fake News Detection via Reinforcement Learningcited by 30
  8. 2017A simple but tough-to-beat baseline for the Fake News Challenge stance detection taskcited by 26
  9. 2020Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repositorycited by 25
  10. 2021Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Documentcited by 19
  11. 2022An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changescited by 15
  12. 2018Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake Newscited by 11
  13. 2019In Search of Credible Newscited by 10

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 2; 2024: 2; 2025: 2; 2026: 2.

10 papers.

  1. 2024Generative Large Language Models in Automated Fact-Checking: A Surveycited by 19
  2. 2023Evaluating Large Language Models for Health-related Queries with Presuppositionscited by 12
  3. 2022SciTweets -- A Dataset and Annotation Framework for Detecting Scientific Online Discoursecited by 9
  4. 2026One Persona, Many Cues, Different Results: How Sociodemographic Cues Impact LLM Personalizationcited by 9
  5. 2022Autonomation, Not Automation: Activities and Needs of European Fact-checkers as a Basis for Designing Human-Centered AI Systemscited by 7
  6. 2025A Scoping Review of Natural Language Processing in Addressing Medically Inaccurate Information: Errors, Misinformation, and Hallucinationcited by 2
  7. 2023Not Enough Labeled Data? Just Add Semantics: A Data-Efficient Method for Inferring Online Health Textscited by 1
  8. 2024FarExStance: Explainable Stance Detection for Farsicited by 1
  9. 2025From Generation to Detection: A Multimodal Multi-Task Dataset for Benchmarking Health Misinformationcited by 1
  10. 2026Integrating Persuasion Theory into the Epidemiological Modelling of Health Misinformation Spread on Social Mediacited by 0