False Claims Detection
False Claims Detection is a methodological framework within fraud detection that identifies and verifies deceptive assertions in structured or unstructured data by distinguishing factually unsupported or intentionally falsified statements from legitimate claims through analytical, statistical, or machine learning techniques.
130
Publications
8.7K
Citations
431
Authors
195
Institutions
Publications per year
2017–2026
86
Parents
130
Knowledge does not protect against illusory truth.
Lisa K. Fazio, Nadia M. Brashier, B. Keith Payne et al. · Journal of Experimental Psychology General · 2015 · 589 citations · Full text
Like-minded sources on Facebook are prevalent but not polarizing
Brendan Nyhan, Jaime E. Settle, Emily Thorson et al. · Nature · 2023 · 309 citations · Full text
Social Sciences, Political Communication, Political Science +15
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431
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195
University of Oxford
Oxford, United Kingdom
5 h-index
13 publications
1.1K citations

The University of Western Australia
Perth, Australia
4 h-index
14 publications
1K citations
Duke University
Durham, United States
4 h-index
13 publications
1.4K citations

University of Notre Dame
Notre Dame, United States
4 h-index
14 publications
852 citations
Max Planck Institute for Informatics
Saarbrücken, Germany
4 h-index
14 publications
2.5K citations
London School of Economics and Political Science
London, United Kingdom
3 h-index
3 publications
60 citations

Cornell University
Ithaca, United States
3 h-index
4 publications
213 citations

University of Warwick
Coventry, United Kingdom
3 h-index
7 publications
1K citations
1–8 of 195
Repository · 4 publications · 75 citations
4
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Repository · 4 publications · 117 citations
4
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3 publications · 273 citations
3
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Repository · 3 publications · 80 citations
3
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TKDE · 2 publications · 44 citations
2
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1–5