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Participants in social media systems must balance many considerations when choosing what to share and with whom. Sharing with others invites certain risks, as well as potential benefits; achieving the right balance is even more critical when sharing photos, which can be particularly engaging, but potentially compromising. In this paper, we examine photo-sharing decisions as an interaction between high-level user preferences and specific features of the images being shared. Our analysis combines insights from a 96-user survey with metadata from 10.4M photos to develop a model integrating these perspectives to predict permissions settings for uploaded photos. We discuss implications, including how such a model can be applied to provide online sharing experiences that are more safe, more scalable, and more satisfying.
Kairam et al. (Thu,) studied this question.
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