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      Mirror, Mirror on the Wall, Who Is the Whitest of All? Racial Biases in Social Media Beauty Filters

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          Abstract

          Digital beauty filters are pervasive in social media platforms. Despite their popularity and relevance in the selfies culture, there is little research on their characteristics and potential biases. In this article, we study the existence of racial biases on the set of aesthetic canons embedded in social media beauty filters, which we refer to as the Beautyverse. First, we provide a historic contextualization of racial biases in beauty practices, followed by an extensive empirical study of racial biases in beauty filters through state-of-the-art face processing algorithms. We show that beauty filters embed Eurocentric or white canons of beauty, not only by brightening the skin color, but also by modifying facial features.

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            DeepFace: Closing the Gap to Human-Level Performance in Face Verification

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              Visualizing and Understanding Convolutional Networks

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                Author and article information

                Contributors
                Journal
                Social Media + Society
                Social Media + Society
                SAGE Publications
                2056-3051
                2056-3051
                April 2024
                April 19 2024
                April 2024
                : 10
                : 2
                Affiliations
                [1 ]ELLIS Alicante, Spain
                [2 ]Alexander von Humboldt Institute for Internet and Society, Germany
                Article
                10.1177/20563051241239295
                ebefe751-f029-4607-aff2-4c863eaafa62
                © 2024

                https://creativecommons.org/licenses/by-nc/4.0/

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