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Sixteen facial expressions occur in similar contexts worldwide

Authors :
Cowen, Alan S.
Keltner, Dacher
Schroff, Florian
Jou, Brendan
Adam, Hartwig
Prasad, Gautam
Source :
Nature. January 14, 2021, Vol. 589 Issue 7841, p251, 7 p.
Publication Year :
2021

Abstract

Understanding the degree to which human facial expressions co-vary with specific social contexts across cultures is central to the theory that emotions enable adaptive responses to important challenges and opportunities.sup.1-6. Concrete evidence linking social context to specific facial expressions is sparse and is largely based on survey-based approaches, which are often constrained by language and small sample sizes.sup.7-13. Here, by applying machine-learning methods to real-world, dynamic behaviour, we ascertain whether naturalistic social contexts (for example, weddings or sporting competitions) are associated with specific facial expressions.sup.14 across different cultures. In two experiments using deep neural networks, we examined the extent to which 16 types of facial expression occurred systematically in thousands of contexts in 6 million videos from 144 countries. We found that each kind of facial expression had distinct associations with a set of contexts that were 70% preserved across 12 world regions. Consistent with these associations, regions varied in how frequently different facial expressions were produced as a function of which contexts were most salient. Our results reveal fine-grained patterns in human facial expressions that are preserved across the modern world. An analysis of 16 types of facial expression in thousands of contexts in millions of videos revealed fine-grained patterns in human facial expression that are preserved across the modern world.<br />Author(s): Alan S. Cowen [sup.1] [sup.2] , Dacher Keltner [sup.1] , Florian Schroff [sup.3] , Brendan Jou [sup.4] , Hartwig Adam [sup.3] , Gautam Prasad [sup.3] Author Affiliations: (1) Department [...]

Details

Language :
English
ISSN :
00280836
Volume :
589
Issue :
7841
Database :
Gale General OneFile
Journal :
Nature
Publication Type :
Academic Journal
Accession number :
edsgcl.650181123
Full Text :
https://doi.org/10.1038/s41586-020-3037-7