The DOI matches its Crossref record; 54 of the 55 references it cites were found in a registry or an index.
Validation of data-driven computational models of social perception of faces.
Abstract
People rapidly form impressions from facial appearance, and these impressions affect social decisions. We argue that data-driven, computational models are the best available tools for identifying the source of such impressions. Here we validate seven computational models of social judgments of faces: attractiveness, competence, dominance, extroversion, likability, threat, and trustworthiness. The models manipulate both face shape and reflectance (i.e., cues such as pigmentation and skin smoothness). We show that human judgments track the models' predictions (Experiment 1) and that the models differentiate between different judgments, though this differentiation is constrained by the similarity of the models (Experiment 2). We also make the validated stimuli available for academic research: seven databases containing 25 identities manipulated in the respective model to take on seven different dimension values, ranging from -3 SD to +3 SD (175 stimuli in each database). Finally, we show how the computational models can be used to control for shared variance of the models. For example, even for highly correlated dimensions (e.g., dominance and threat), we can identify cues specific to each dimension and, consequently, generate faces that vary only on these cues.
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“A second limitation was that we only used male Caucasian faces. This decision was made in the light of evidence that there is a bias to classify bald, hairless faces as males (Todorov et al., 2013); thus, it is possible that our findings may not extend to females faces as well as faces from different ethnic backgrounds.”
From Mistrust and negative self‐esteem: Two paths from attachment styles to paranoia. (2021) · cites this paper as Todorov et al., 2013
In the citing paper
“The choice of using intelligence, trustworthiness, sociability and happiness as dependent attributes for the halo effect was driven by existing literature on this cognitive bias, such as [4,6,8,9,22,53,60–63].”
From What is beautiful is still good: the attractiveness halo effect in the era of beauty filters (2024) · cites this paper as [63]
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Social Attributions from Faces: Determinants, Consequences, Accuracy, and Functional Significance
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Inferring Character From Faces
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Metadata
- Authors
- Todorov, A., Dotsch, R., Porter, J. M., Oosterhof, N. N., & Falvello, V. B.
- Affiliations
- Princeton University (US)
- Columbia University (US)
- University of Trento (IT)
- Venue
- Emotion
- Published
- 2013-08
- Volume
- 13
- Issue
- 4
- Pages
- 724-738
- ISSN
- 1528-3542 (ISSN-L)
- 1931-1516
- OpenAlex
- W2140051380
- Cited by
- 226
- References
- 55
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 13 · 2023: 22 · 2022: 12 · 2021: 36 · 2020: 27 · 2019: 25 · 2018: 25 · 2017: 18 · 2016: 11 · 2015: 13 · 2014: 5 · 2013: 2
- FWCI
- 5.65
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Emotion (publishedVersion)
- PubMed (publishedVersion)
- Institutional Research Information System (Università degli Studi di Trento) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Evolutionary Psychology and Human Behavior
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Keywords
- face perception, computational model, model validation, facial attractiveness, perceived competence, perceived dominance, likeability, threat perception, perceived trustworthiness, facial shape, pigmentation, skin smoothness, face database
- MeSH terms
- Adult, Computer Simulation, Cues, Face, Facial Expression, Female, Humans, Male, Models, Psychological, Pattern Recognition, Visual, Social Perception, Databases, Factual, Young Adult
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