Fooled by the fakes: Cognitive differences in perceived claim accuracy and sharing intention of non-political deepfakes
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Overall, deepfake detection does not seem to vary based on gender, education, income, or profession.
“Overall, deepfake detection does not seem to vary based on gender, education, income, or profession [7, 32, 37].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
Cognitive ability and analytical thinking are positively associated with detection accuracy.
“Cognitive ability and analytical thinking are positively associated with detection accuracy [32, 23].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
Other studies have found no relationship between deepfake detection and age.
“In contrast, other studies have found no relationship between detection and age [32, 33, 37].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
Providing warnings that a video might be faked is associated with increased accuracy ratings.
“Providing warnings that a video might be faked is associated with increased accuracy ratings [32].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
Political interest or partisanship has no association with deepfake detection performance across most studies.
“Overall, political interest and partisanship do not appear to have an impact on detection [23, 32].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
Higher cognitive ability is associated with better deepfake detection.
“At the person level, higher cognitive ability, analytical thinking skills, and the tendency not to accept information at face value are all associated with better deepfake detection [23, 32].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
The tendency not to accept information at face value is associated with better deepfake detection.
“At the person level, higher cognitive ability, analytical thinking skills, and the tendency not to accept information at face value are all associated with better deepfake detection [23, 32].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
Studies into the effects of ethnicity and age yield inconsistent results.
“while studies into the e ff ects of ethnicity and age yield inconsistent results [32, 37, 43].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
Interest in and knowledge of politics and political distrust demonstrate inconsistent effects on detection performance.
“Interest in and knowledge of politics and political distrust demonstrate inconsistent e ff ects on detection performance [23, 32], so too do intuition and emotional arousal [2, 27].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
Demographic factors such as gender, education, and income level appear to have no discernible effect on detection performance.
“Demographic factors such as gender, education, and income level appear to have no discernible e ff ect on detection performance [7, 32, 37, 42]”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
Analytical thinking skills are associated with better deepfake detection.
“At the person level, higher cognitive ability, analytical thinking skills, and the tendency not to accept information at face value are all associated with better deepfake detection [23, 32].”
From Human Performance in Deepfake Detection: A Systematic Review (2025) · cites this paper as [32]
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References 12 · Cited by 71
- Authors
- Ahmed, S.
- Affiliations
- Nanyang Technological University (SG)
- Corresponding author
- Ahmed, Saifuddin
- ORCID
- Ahmed, Saifuddin
- Venue
- Personality and Individual Differences
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 182
- Pages
- 111074
- ISSN
- 0191-8869 (ISSN-L)
- OpenAlex
- W3177228617
- Cited by
- 71
- References
- 12
- Citations by year
- 2026: 14 · 2025: 17 · 2024: 17 · 2023: 14 · 2022: 9
- FWCI
- 13.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Personality and Individual Differences (publishedVersion)
- DR-NTU (Nanyang Technological University) (submittedVersion)
- Funders
- Nanyang Technological University
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Psychology › Social Psychology › Deception detection and forensic psychology
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Keywords
- deepfakes, sharing intention, cognitive ability, individual differences, disinformation, social media influencers, misinformation sharing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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