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Four dimensions characterize attributions from faces using a representative set of English trait words
People readily (but often inaccurately) attribute traits to others based on faces. While the details of attributions depend on the language available to describe social traits, psychological theories argue that two or three dimensions (such as valence and dominance) summarize social trait attributio...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397784/ https://www.ncbi.nlm.nih.gov/pubmed/34453054 http://dx.doi.org/10.1038/s41467-021-25500-y |
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author | Lin, Chujun Keles, Umit Adolphs, Ralph |
author_facet | Lin, Chujun Keles, Umit Adolphs, Ralph |
author_sort | Lin, Chujun |
collection | PubMed |
description | People readily (but often inaccurately) attribute traits to others based on faces. While the details of attributions depend on the language available to describe social traits, psychological theories argue that two or three dimensions (such as valence and dominance) summarize social trait attributions from faces. However, prior work has used only a small number of trait words (12 to 18), limiting conclusions to date. In two large-scale, preregistered studies we ask participants to rate 100 faces (obtained from existing face stimuli sets), using a list of 100 English trait words that we derived using deep neural network analysis of words that have been used by other participants in prior studies to describe faces. In study 1 we find that these attributions are best described by four psychological dimensions, which we interpret as “warmth”, “competence”, “femininity”, and “youth”. In study 2 we partially reproduce these four dimensions using the same stimuli among additional participant raters from multiple regions around the world, in both aggregated and individual-level data. These results provide a comprehensive characterization of trait attributions from faces, although we note our conclusions are limited by the scope of our study (in particular we note only white faces and English trait words were included). |
format | Online Article Text |
id | pubmed-8397784 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-83977842021-09-22 Four dimensions characterize attributions from faces using a representative set of English trait words Lin, Chujun Keles, Umit Adolphs, Ralph Nat Commun Article People readily (but often inaccurately) attribute traits to others based on faces. While the details of attributions depend on the language available to describe social traits, psychological theories argue that two or three dimensions (such as valence and dominance) summarize social trait attributions from faces. However, prior work has used only a small number of trait words (12 to 18), limiting conclusions to date. In two large-scale, preregistered studies we ask participants to rate 100 faces (obtained from existing face stimuli sets), using a list of 100 English trait words that we derived using deep neural network analysis of words that have been used by other participants in prior studies to describe faces. In study 1 we find that these attributions are best described by four psychological dimensions, which we interpret as “warmth”, “competence”, “femininity”, and “youth”. In study 2 we partially reproduce these four dimensions using the same stimuli among additional participant raters from multiple regions around the world, in both aggregated and individual-level data. These results provide a comprehensive characterization of trait attributions from faces, although we note our conclusions are limited by the scope of our study (in particular we note only white faces and English trait words were included). Nature Publishing Group UK 2021-08-27 /pmc/articles/PMC8397784/ /pubmed/34453054 http://dx.doi.org/10.1038/s41467-021-25500-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lin, Chujun Keles, Umit Adolphs, Ralph Four dimensions characterize attributions from faces using a representative set of English trait words |
title | Four dimensions characterize attributions from faces using a representative set of English trait words |
title_full | Four dimensions characterize attributions from faces using a representative set of English trait words |
title_fullStr | Four dimensions characterize attributions from faces using a representative set of English trait words |
title_full_unstemmed | Four dimensions characterize attributions from faces using a representative set of English trait words |
title_short | Four dimensions characterize attributions from faces using a representative set of English trait words |
title_sort | four dimensions characterize attributions from faces using a representative set of english trait words |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397784/ https://www.ncbi.nlm.nih.gov/pubmed/34453054 http://dx.doi.org/10.1038/s41467-021-25500-y |
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