Analyzing Privacy Dynamics within Groups using Gamified Auctions

Online shared content, such as group pictures, often contains information about multiple users. Developing technical solutions to manage the privacy of such "co-owned" content is challenging because each co-owner may have different preferences. Recent technical approaches advocate group-decision mechanisms, including auctions, to decide as how best to resolve these differences. However, it is not clear if users would participate in such mechanisms and if they do, whether they would act altruistically. Understanding the privacy dynamics is crucial to develop effective mechanisms for privacy-respecting collaborative systems. Accordingly, this work develops RESOLVE, a privacy auction game to understand the sharing behavior of users in groups. Our results of users' playing the game show that i) the users' understanding of individual vs. group privacy differs significantly; ii) often users fight for their preferences even at the cost of others' privacy; and iii) at times users collaborate to fight for the privacy of others.