A wealth of social information produced by online social networks and user-generated content sharing services is currently fragmented across many different proprietary applications. Combined, it could provide a more accurate representation of the social world that can be leveraged to enable novel socially-aware applications. We introduce Prometheus, a peer-to-peer service that collects social information from multiple sources into a distributed multigraph and exposes it through an interface that implements non-trivial social inferences. The system's socially-aware design serves multiple purposes. First, it allows users to manage their social information via socially-trusted peers, thus improving service availability. Second, it exploits naturally-formed social groups for improved end-to-end social inference performance and reduced message overhead. Third, it reduces the opportunity of malicious peers to influence requests in the system, thus constituting a more resilient solution to attacks.

Social applications can mine the Prometheus social graph to improve performance in search, provide recommendations, allow resource sharing and increase data privacy. The traversal of the de-centralized social graph in the network translates into a socially-informed routing in the peer-to-peer layer. We define the projection graph, the result of decentralizing a social graph onto a peer-to-peer network, and study its network properties (degree, node and edge betweenness centrality) and how they can be used to improve application and system performance. Experimental evaluation on real networks demonstrates the association between the properties of the social graph and the projection graph, and that the properties of the (dynamic) projection graph can be inferred from the properties of the (slower changing) social graph. Furthermore, it demonstrates with two application scenarios the usability of the projection graph in designing social search applications and unstructured P2P overlays.