Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29742
Appears in Collections:Psychology Journal Articles
Peer Review Status: Refereed
Title: Comparing theory-driven and data-driven attractiveness models using images of real women's faces
Author(s): Holzleitner, Iris J
Lee, Anthony J
Hahn, Amanda C
Kandrik, Michal
Bovet, Jeane
Renoult, Julien P
Simmons, David
Garrod, Oliver
DeBruine, Lisa M
Jones, Benedict C
Contact Email: anthony.lee@stir.ac.uk
Keywords: mate preferences
principal component analysis
face perception
face processing
Issue Date: Dec-2019
Citation: Holzleitner IJ, Lee AJ, Hahn AC, Kandrik M, Bovet J, Renoult JP, Simmons D, Garrod O, DeBruine LM & Jones BC (2019) Comparing theory-driven and data-driven attractiveness models using images of real women's faces. Journal of Experimental Psychology: Human Perception and Performance, 45 (12), pp. 1589-1595. https://doi.org/10.1037/xhp0000685
Abstract: Facial attractiveness plays a critical role in social interaction, influencing many different social outcomes. However, the factors that influence facial attractiveness judgments remain relatively poorly understood. Here, we used a sample of 594 young adult female face images to compare the performance of existing theory-driven models of facial attractiveness and a data-driven (i.e., theory-neutral) model. Our data-driven model and a theory-driven model including various traits commonly studied in facial attractiveness research (asymmetry, averageness, sexual dimorphism, body mass index, and representational sparseness) performed similarly well. By contrast, univariate theory-driven models performed relatively poorly. These results (1) highlight the utility of data driven models of facial attractiveness and (2) suggest that theory-driven research on facial attractiveness would benefit from greater adoption of multivariate approaches, rather than the univariate approaches that they currently almost exclusively employ.
DOI Link: 10.1037/xhp0000685
Rights: ¬©American Psychological Association, 2019. This paper is not the copy of record and may not exactly replicate the authoritative document published in the APA journal. Please do not copy or cite without author's permission. The final article is available, upon publication, at: https://doi.org/10.1037/xhp0000685

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