Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/38389
Appears in Collections:Psychology Journal Articles
Peer Review Status: Refereed
Title: A four component model for the social perception of first names.
Author(s): Lee, Anthony
Lis, Odette
Panagiotakou, Sofia
Contact Email: anthony.lee@stir.ac.uk
Keywords: given names
person perception
stereotypes
bias
valence-dominance model
stereotype content model
Issue Date: 15-Jul-2026
Date Deposited: 6-Oct-2026
Citation: Lee A, Lis O & Panagiotakou S (2026) A four component model for the social perception of first names.. <i>Social Cognition</i>. https://doi.org/10.1521/soco.2026.44.5.1
Abstract: First (given) names are subject to stereotypes and can be a source of bias when making many important decisions. However, previous research on name bias is fragmented and informed by disjointed theories. Here, we investigate the underlying structure of name biases to provide a unifying theory of the social perception of names. Across two samples collected in separate European countries (UK and Germany; N = 1083 and 972 respectively), male and female names were rated on multiple social traits, with mean trait ratings for each name then being entered into a Principal Components Analysis. In both samples, and for both male and female names, the same four component structure was found: these included components corresponding with valence/competence, dominance/warmth, youth/attractiveness, and familiarity. We propose that this four component model could provide an overarching theoretical framework that could help unite research on name bias and generate new testable hypotheses.
DOI Link: 10.1521/soco.2026.44.5.1
Rights: This is the Author Accepted Manuscript of Lee, A., Lis, O., & Panagiotakou, S. (2026). A four component model for the social perception of first names. Social Cognition. Advance online publication. The manuscript has been accepted for publication following peer review but has not undergone the publisher’s copyediting or typesetting. © 2026 . All rights reserved. The published version of record is available at https://doi.org/10.1521/soco.2026.44.5.1
Licence URL(s): https://storre.stir.ac.uk/STORREEndUserLicence.pdf

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