An Algorithm to Condense Social Networks and Identify Brokers

Abstract

In social network analysis the identification of communities and the discovery of brokers is a very important issue. Community detection typically uses partition techniques. In this work the information extracted from social networking goes beyond cohesive groups, enabling the discovery of brokers that interact between communities. The partition is found using a set covering formulation, which allows the identification of actors that link two or more dense groups. Our algorithm returns the needed information to create a good visualization of large networks, using a condensed graph with the identification of the brokers