Abstract
Human facial attractiveness is evaluated by using multiple cues. Among others, sexual dimorphism (i.e. masculinity for male faces/femininity for female faces) is an influential factor of perceived attractiveness. Since facial attractiveness is judged by incorporating sexually dimorphic traits as well as other cues, it is theoretically possible to dissociate sexual dimorphism from facial attractiveness. This study tested this by using a data-driven mathematical modelling approach. We first analysed the correlation between perceived masculinity/femininity and attractiveness ratings for 400 computer-generated male and female faces (Experiment 1) and found positive correlations between perceived femininity and attractiveness for both male and female faces. Using these results, we manipulated a set of faces along the attractiveness dimension while controlling for sexual dimorphism by orthogonalisation with data-driven mathematical models (Experiment 2). Our results revealed that perceived attractiveness and sexual dimorphism are dissociable, suggesting that there are as yet unidentified facial cues other than sexual dimorphism that contribute to facial attractiveness. Future studies can investigate the true preference of sexual dimorphism or the genuine effects of attractiveness by using well-controlled facial stimuli like those that this study generated. The findings will be of benefit to the further understanding of what makes a face attractive.
Highlights
Human facial attractiveness is evaluated by using multiple cues
In order to confirm that datadriven manipulation of facial features associated with sexual dimorphism would successfully predict perceived masculinity/femininity, we analysed the rating scores of sexual dimorphism with the hierarchical Bayesian regression models
The perceived masculinity/femininity rating score for female faces significantly changed with the model-based facial feature manipulation irrespective of the sex of raters (Linear term = 0.97, 95% credible interval (CrI) = [0.85 to 1.09]; Quadratic term = −0.03, 95% CrI = [− 0.08 to 0.01])
Summary
Human facial attractiveness is evaluated by using multiple cues. Among others, sexual dimorphism (i.e. masculinity for male faces/femininity for female faces) is an influential factor of perceived attractiveness. Feminine-looking men, more than masculine-looking men, are willing to devote their parental investment to their offspring in order to increase the chance of their offspring’s survival (i.e. good dad traits;[24]) Such a trade-off between preference for a good gene and a good dad makes male facial attractiveness judgments more complicated. Many studies on the effect of sexual dimorphism on perceived attractiveness have employed face morphing methods to increase or decrease facial femininity/masculinity. Such methods eliminate natural variations in other important cues[25], which are often important determinants of facial impressions[1,26]. This suggests that data-driven modelling has great potential for discovering as yet unidentified facial cues to attractiveness, which have far been overlooked by hypothesis-driven research
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