A Social Identity Approach to Identify Familiar Strangers in a Social Network

Abstract

We present a novel problem of searching for ‘familiar strangers’ in a social network. Familiar strangers are individuals who are not directly connected but exhibit some similarity. The power-law nature of social networks determines that majority of individuals are directly connected with a small number of fellow individuals, and similar individuals can be largely unknown to each other. Moreover, the individuals of a social network have only a local view of the network, which makes the problem of aggregating these familiar strangers a challenge. In this work, we formulate the problem, show why it is significant to address the challenge, and present an approach that innovatively employs the social identities of the individuals with competitive approaches. A blogger and citation network are used to showcase technical details and empirical results with related issues and future work.