Discovering unique members from mobile social networks

The exponential growth of users in Mobile Telecom Network has forced operators to analyze their network more frequently to predict changes in user behavior and offer right incentives to retain them in their network. In this paper, we propose a self-contained approach to the problem of analyzing the community structure to identify bridge members in the community and also to understand their diffusion behavior into the network. We have used call graphs of telecom network to discover the presence of highly ranked unique members inside the community for targeted advertisements. Three different techniques were applied related to this connection and their dissipation strength is compared for its importance. We present our experimental results with indicative services to mobile networks.