Privacy-preserving concepts for supporting recommendations in decentralized OSNs

Recommender systems depend on the amount of available and processable information for a given purpose. Trends towards decentralized online social networks (OSNs), promising more user control by means of privacy preserving mechanisms, lead to new challenges for (social) recommender systems. Information, recommender algorithms rely on, is no longer available, (i.e. central user registries, friends of friends), thus shared data is reduced and centralized processing becomes difficult. In this paper we address such drawbacks based on identified needs in the decentralized OSN di.me and present concepts overcoming those for selected functionalities. Besides this, we tackle the support of privacy advisory, warning the user of risks when sharing data.