You trust a face like yours

Tamami Nakano () and Takuto Yamamoto
Additional contact information
Tamami Nakano: Osaka University
Takuto Yamamoto: Osaka University

Palgrave Communications, 2022, vol. 9, issue 1, 1-6

Abstract: Abstract The appraisal of trustworthiness from facial appearance of a stranger is critical for successful social interaction. Although self-resemblance is considered a significant factor affecting the perception of trustworthiness, research is yet to be conducted on whether this theory is applicable to natural unfamiliar faces in real life. We examined this aspect by using a state-of-the-art deep convolutional neural network for face recognition to measure the facial similarity of a large sample of people with the evaluators. We found that the more they resembled the rater, the more trustworthy they were evaluated if they were of the same sex as the rater. Contrarily, when the stranger was of the opposite sex, self-resemblance did not affect trustworthiness ratings. These results demonstrate that self-resemblance is an important factor affecting our social judgments of especially same-sex people in real life.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1057/s41599-022-01248-8 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01248-8

Ordering information: This journal article can be ordered from
https://www.nature.com/palcomms/about

DOI: 10.1057/s41599-022-01248-8

Access Statistics for this article

More articles in Palgrave Communications from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().