Leveraging personal photos to inferring friendships in social network services

Social network services have become widely used as an important tool to share rich information; in such networks, making new friends is the most basic functionality to enable users to take advantage of their social networks. In this paper we look into personal photos as an additional source for social network analysis and analyze the potential of people tags in the photos for friend recommendations. We also propose a new compact data structure, collectively called Face Co-Occurrence Networks (FCON), which stores crucial and quantitative information about people’s appearance in photos. We discover strong associative relationships among people and recommend reliable social friends by utilizing FCON. Experimental results demonstrate the effectiveness and efficiency of our method for recommending friends in social network services.

► A network-formed compact structure is modeled for discovering frequent patterns in photo tagging.
► We leverage people tags in personal photos as indicators of social relationships.
► We examine the effectiveness and efficiency of the network-centric model for recommending social networking friends.
► Co-appearance information in the photos can make compelling recommendations.