A Crowdsourced Evaluation of Facial Averageness and Attractiveness

Abstract

Background: Evolutionary psychologists have demonstrated that humans are attracted to individuals who possess average anatomy for the population.

Objectives: The aim of this study was to prove that a composite of average facial features would be more attractive to raters than the cohort utilized to create the composite.

Methods: The male and female cohorts each consisted of 41 standardized frontal-view monochrome photographs, with 1 composite image derived from the other 40 real images. Amazon Mechanical Turk, a widely used crowdsourcing platform, was utilized to obtain ratings of images ranging from 1 to 7, with 1 and 7 being least and most attractive, respectively. The strength of the preference for the composite over the real images was assessed by the difference between the mean rating of the composite and real images.

Results: In total, 870 and 876 respondents were recruited to rate the male and female cohorts, respectively. For the male and female cohorts, the composite image was rated significantly higher than the rest of the cohort overall and across all ages, genders, and countries of residence (all P < 0.0001). For both cohorts, the strength of the preference was significantly higher for European respondents and lower for South American and nonbinary respondents (all P < 0.05).

Conclusions: This study reveals that average facial anatomy is perceived as most attractive across all demographics, a finding that is hoped to serve as a stepping stone for further studies leading to objective cosmetic quantifications and integrating evidence-based medicine into aesthetic surgery.