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The physical environment you navigate strongly determines which communitiesand people matter most to individuals. These effects drive both personal accessto opportunities and the social capital of communities, and can often beobserved in the personal mobility traces of individuals. Traditional socialmedia feeds underutilize these mobility-based features, or do so in a privacyexploitative manner. Here we propose a consent-first private informationsharing paradigm for driving social feeds from users' personal private data,specifically using mobility traces. This approach designs the feed toexplicitly optimize for integrating the user into the local community and forsocial capital building through leveraging mobility trace overlaps as a proxyfor existing or potential real-world social connections, creatingproportionality between whom a user sees in their feed, and whom the user islikely to see in person. These claims are validated against existingsocial-mobility data, and a reference implementation of the proposed algorithmis built for demonstration. In total, this work presents a novel technique fordesigning feeds that represent real offline social connections through privateset intersections requiring no third party, or public data exposure.

Building a healthier feed: Private location trace intersection driven feed recommendations