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        "A whole new way to see yourself(ie)": Exploring how face filters transform the practice of selfie creation

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        Publication date
        2018
        Author
        Schipper, M.
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        Summary
        In 2015, Snapchat launched the face filters feature and promoted it as “a whole new way to see yourself(ie)” (Snap Inc. 2015). Ever since, the feature has been copied by many platforms and the use of interactive face filters has rapidly become part of selfie culture. Face filters are known to convey stereotypical norms of beauty, femininity and self-presentation, but also instigate new ways of experimental selfie creation. However, academic research on pre-made figurative face filters and how they change the contemporary practice of selfie creation is lacking. This thesis fills this gap by exploring how face filters change the conventional practices of selfie creation, how gender- stereotypical selfie creation is confirmed or disrupted by those filters, and how this may lead to liberated or suppressed practices of selfie creation. Qualitative and quantitative methods are combined to analyze the differences between two datasets of selfies, collected from the hashtags #selfie and #filterselfie on Instagram. Face detection software is used to measure the selfies, and manual categorization of the datasets is executed to gather data about gender and facial expressions. As a result, this thesis offers an overview of the different ways in which face filters may be liberating or suppressing, and how it changes conventional gender display. It concludes that most practices of so-called liberation of conventions are caused by the filters’ affordances rather than intentional subversion of conventions by users themselves. In line with Barnard’s (2016) concept of the (dis)empowerment paradox, it also concludes that face filters may be liberating on an individual level, while they simultaneously reinforce the cultural conventions of gender display and self- portrayal. Additionally, the methodological reflection in this thesis offers insights and proposes enhancements for the use of computational methods as a means to analyze visual culture within the humanities.
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        https://studenttheses.uu.nl/handle/20.500.12932/32595
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