2017
DOI: 10.1177/0956797617716929
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Facial Width-to-Height Ratio Does Not Predict Self-Reported Behavioral Tendencies

Abstract: A growing number of studies have linked facial width-to-height ratio (fWHR) with various antisocial or violent behavioral tendencies. However, those studies have predominantly been laboratory based and low powered. This work reexamined the links between fWHR and behavioral tendencies in a large sample of 137,163 participants. Behavioral tendencies were measured using 55 well-established psychometric scales, including self-report scales measuring intelligence, domains and facets of the five-factor model of pers… Show more

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Cited by 76 publications
(71 citation statements)
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References 30 publications
(44 reference statements)
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“…Next, we used the Face++ application (Megvii Inc., http://www.faceplusplus.com) to classify the hosts' race, age, and smile intensity. Face++ is a commercial algorithm that has been used in previous research to extract various indicators from large numbers of face images (Edelman, Luca, & Svirsky, 2017;Kosinski, 2017). For example, Edelman and colleagues (2017) used Face++ to classify the race of Airbnb guests.…”
Section: Photo Classificationmentioning
confidence: 99%
“…Next, we used the Face++ application (Megvii Inc., http://www.faceplusplus.com) to classify the hosts' race, age, and smile intensity. Face++ is a commercial algorithm that has been used in previous research to extract various indicators from large numbers of face images (Edelman, Luca, & Svirsky, 2017;Kosinski, 2017). For example, Edelman and colleagues (2017) used Face++ to classify the race of Airbnb guests.…”
Section: Photo Classificationmentioning
confidence: 99%
“…The nose to eyes distance was shown to correlate with preferences in an inverted U-shape (Pallett et al, 2010), whilst the Midface range (corresponding with this feature) had no correlation with preference (Cunningham, 1986). For fWHR, a recent large sample study claimed for a null effect for this feature (Kosinski, 2017).…”
Section: Discussionmentioning
confidence: 85%
“…The width to height ratio (fWHR) (Weston, Friday, & Liò, 2007), was originally proposed as an evolutionary sexual marker (being greater for males) and was associated with aggressive and unethical behavior (e.g. Geniole, Keyes, Carré, & McCormick, 2014 but see Kosinski, 2017). Two other studies showed that changing the distance between local face elements (between the two eyes and between the eyes and nose) had a meaningful effect on preferences (Pallett, Link, & Lee, 2010).…”
Section: Visual Features Contribute Differently To Preferences For DImentioning
confidence: 99%
“…Automated procedures offer a new solution to the classification of face images. While automated face classification has received considerable attention in the computer science literature, social scientists have only recently begun to utilize the technology (e.g., Edelman et al, 2017;Kosinski, 2017;Rhue & Clark, 2016). Crucially, relying on an algorithm allows researchers to work with large data sets and reduces the time spent on data collection.…”
Section: Automated Classification Of Demographics From Face Images:mentioning
confidence: 99%
“…We provided first evidence for their validity here, but future studies need to test the algorithms under different conditions. For example, while we tested the algorithms' accuracy in classifying variable images taken from the internet, future studies should look at accuracy levels for profile photos from Facebook or Airbnb, which have been used in recent research (Edelman et al, 2017;Jaeger, Sleegers, Evans, Stel, & van Beest, 2018;Kosinski, 2017 , 2017). This approach would also address a limitation of the present study in which the APIs' classifications of some dimensions were compared against averaged ratings by humans rather than self-reports.…”
Section: Advantages and Limitations Of Using Face Classification Apismentioning
confidence: 99%