Individual differences in learning the affective value of others under minimal conditions.
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This paper provides the first demonstration that people can learn about the positive and negative value of other people (e.g., neutral faces) under minimal learning conditions, with stable individual differences in this learning. In four studies, participants viewed neutral faces paired with sentences describing positive, negative or neutral behaviors on either two (Study 1) or four (Studies 2, 3, and 4) occasions. Participants were later asked to judge the valence of the faces alone. Studies 1 and 2 demonstrated that learning does occur under minimal conditions. Study 3 and 4 further demonstrated that the degree of learning was moderated by Extraversion. Finally, Study 4 demonstrated that initial learning persisted over a period of 2 days. Implications for affective processing and person perception are discussed.
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Individuals paired with positive valence characteristics are rated as more likeable and approachable, and the opposite occurs for those with negative information.
“Individuals paired with positive valence characteristics are rated as more likeable and approachable but the opposite for those with negative information (22).”
From Oxytocin, the peptide that bonds the sexes also divides them (2016) · cites this paper as [22]
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A beautiful face is good when we’re judged by others, a moral character is better
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Memory for incidentally perceived social cues: Effects on person judgment
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Attenuating social affective learning effects with Memory Suppression manipulations
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An application of Heider's P–O–X balance model to change evaluative conditioning effects
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Interpersonal Pupillometry: The Pupil as an Indicator of Emotion and Its Utility as a Social Cue
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Impression Formation Based on Face: From the Perspective of Neuroscience
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The Impact of Facial Attractiveness and Affective Person Knowledge on Visual Awareness
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Rapid Detection of Neutral Faces Associated With Emotional Value Among Older Adults
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Sex differences in the rapid detection of neutral faces associated with emotional value
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Recognising others: Adaptive changes to person recognition throughout the lifespan
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Positive Affective Learning Improves Memory
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Emotional news affects social judgments independent of perceived media credibilityPreprint
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Learning the Affective Value of Others
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Emotional news affects social judgments independent of perceived media credibilityPreprint
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Rahman, R. A., & Eiserbeck, A. (2020) · OSF Preprints (OSF Preprints)
Rahman, R. A., & Baum, J. (2023) · OSF Preprints (OSF Preprints)
- Authors
- Bliss-Moreau, E., Barrett, L. F., & Wright, C. I.
- Affiliations
- Boston College (US)
- Harvard University (US)
- Venue
- Emotion
- Published
- 2008
- Volume
- 8
- Issue
- 4
- Pages
- 479-493
- ISSN
- 1528-3542 (ISSN-L)
- 1931-1516
- PMC
- PMC2761963
- OpenAlex
- W2105963895
- Cited by
- 82
- References
- 72
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 8 · 2022: 5 · 2021: 5 · 2020: 11 · 2019: 1 · 2018: 6 · 2016: 10 · 2015: 3 · 2014: 6 · 2013: 6 · 2012: 7
- FWCI
- 1.72
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Emotion (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Science Foundation (BCS 0527440)
- National Institute of Mental Health (K02 MH001981)
- National Institutes of Health (DP1OD003312)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Evolutionary Psychology and Human Behavior
- Keywords
- individual differences, extraversion, person perception, emotional processing, neutral faces, learning persistence
- MeSH terms
- Adult, Affect, Environment, Extraversion, Psychological, Facial Expression, Female, Humans, Learning, Male, Social Perception
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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.
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