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Jessica Taubert, Erik Van der Burg, David Alais; Are we looking for love in all the wrong faces?. Journal of Vision 2016;16(12):494. https://doi.org/10.1167/16.12.494.
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© ARVO (1962-2015); The Authors (2016-present)
Millions of people use online dating sites each day, scanning through streams of unfamiliar faces in search of an attractive mate. Face images, like most visual stimuli, are subject to processing whereby the current percept is altered by exposure to previous visual input. Recent studies using rapid sequences of faces have found that perception of face identity is biased towards recently seen faces, promoting identity-invariance over time. Here we examine whether the attractiveness of a face is contingent upon the attractiveness of a recently seen face. We designed a binary task mimicking the selection interface popular in online dating websites in which observers typically make binary decisions (attractive or unattractive) about each face in a sequence of unfamiliar faces. Interestingly, even though we used images from an online dating site, the attractiveness of a face depended on the attractiveness of the face on the preceding trial. That is, a face was rated as more attractive when the face on the preceding trial was more attractive compared to average, and less attractive if the preceding face was less attractive. In a second experiment we examined whether the inter-trial attractiveness effect is due to a perceptual phenomenon or a response bias by manipulating face orientation (inverted or upright). Interestingly, we replicated the inter-trial effect, but only when the preceding trial's face had the same orientation as the current trial's face (both inverted, or both upright), suggesting that the effect is due to a perceptual phenomenon. Our results demonstrate that judgments of face attractiveness are influenced by information from our evaluative and perceptual history and that these influences impact our behaviour in the context of binary classifications commonly used in online dating.
Meeting abstract presented at VSS 2016
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