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Casey McGlasson, Jared Lorince, David J. Crandall, Peter M. Todd; Exploring the use of big data in color preference research. Journal of Vision 2013;13(9):1167. doi: https://doi.org/10.1167/13.9.1167.
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© ARVO (1962-2015); The Authors (2016-present)
The study of human color preferences, as well as the color preferences of other species, has long been an active area of research in psychology. However, these studies have been various in their methods and results. Researchers disagree about the ultimate and proximate causes of color preferences, as well as the ultimate and proximate causes of differences in color preference between groups, such as males and females. The purpose of this study is to evaluate the claim that sex differences in color preference exist using a novel implicit method, as well as to explore the possibility of functional, adaptive values associated with sex-specific color preferences. We propose a data-mining approach to studying color preferences using a dataset of more than 100 million photographs from Flickr, an online photo-sharing system. By analyzing the color spectra of photographs that specific populations of interest choose to upload, such as male and female users, we can assess color preferences in an implicit (behavior-based) rather than explicit (ratings-based) manner and on a much larger scale than can be done in a laboratory context or through survey techniques. Using this method, we find strong overall sex differences for the predominant reddish and bluish hues, with women uploading more photos with more reddish pixels and men uploading more photos with more bluish pixels. Finally, by contacting a self-organized community of ‘color-blind photographers’ on Flickr, we explore the relationship between sex-specific color preferences and sex-linked color vision defects (such as red-green color blindness).
Meeting abstract presented at VSS 2013
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