A Social Identity Approach to Identify Familiar Strangers in a Social Network Nitin Agarwal, Huan Liu, Sudheendra Murthy, Arunabha Sen, and Xufei Wang School of Computing and Informatics Arizona State University fNitin.Agarwal.2, Huan.Liu, sudhi, asen,
[email protected] Abstract distribution it is quite likely that they may not know each other. Aggregating such familiar strangers could form a We present a novel problem of searching for ‘familiar critical mass such that (1) the understanding of one mem- strangers’ in a social network. Familiar strangers are individ- uals who are not directly connected but exhibit some similar- ber gives us a sensible and representative glimpse to oth- ity. The power-law nature of social networks determines that ers, (2) more data about familiar members can be collected majority of individuals are directly connected with a small for better customization and services (e.g., personalization number of fellow individuals, and similar individuals can be and recommendation), (3) the nuances among them suggest largely unknown to each other. Moreover, the individuals of new business opportunities, and (4) knowledge about them a social network have only a local view of the network, which can facilitate predictive modeling and trend analysis in new makes the problem of aggregating these familiar strangers a product/market development. Connecting them to form a challenge. In this work, we formulate the problem, show why critical mass can only potentially expand their social net- it is significant to address the challenge, and present an ap- work, i.e., job searching, special interest group formation. proach that innovatively employs the social identities of the Aggregating familiar strangers can encourage participation individuals with competitive approaches.