Textual Misinformation Detection
Textual Misinformation Detection is a computational methodology within natural language processing that specifically identifies and verifies false or misleading claims in textual content by analyzing linguistic patterns and factual consistency.
126
Publications
6.6K
Citations
446
Authors
186
Institutions
Publications per year
2017–2026
122
Parents
126
Fake News Detection Using Machine Learning Ensemble Methods
Iftikhar Ahmad, Muhammad Murtaza Yousaf, Suhail Yousaf et al. · Complexity · 2020 · 466 citations · Full text
DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning
Kashyap Popat, Subhabrata Mukherjee, Andrew Yates et al. · 2018 · 280 citations · Full text
Credibility Assessment of Textual Claims on the Web
Kashyap Popat, Subhabrata Mukherjee, Jannik Strötgen et al. · 2016 · 179 citations
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446
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186
Max Planck Institute for Informatics
Saarbrücken, Germany
4 h-index
12 publications
1.7K citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
11 publications
786 citations
University of Sheffield
Sheffield, United Kingdom
3 h-index
6 publications
318 citations

Wrocław University of Science and Technology
Wroclaw, Poland
3 h-index
4 publications
438 citations
AGH University of Krakow
Krakow, Poland
3 h-index
8 publications
796 citations
University of Chinese Academy of Sciences
Beijing, China
3 h-index
12 publications
593 citations

Delhi Technological University
New Delhi, India
3 h-index
6 publications
186 citations

Taiyuan University of Technology
Taiyuan, China
2 h-index
5 publications
285 citations
1–8 of 186
Repository · 14 publications · 617 citations
11
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4 publications · 436 citations
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3 publications · 259 citations
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2 publications · 122 citations
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2 publications · 82 citations
2
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