Social network classifier for churn prediction in telecom data

Telecom Social Network Analysis (TSNA) is a set of research procedures for identifying structural and behavioral pattern in systems based on the relations among customers. Grounded in graph and system theories, this approach has proven to be a powerful tool for studying networks of social world. This paper addresses the Social position of each customer in a network and Equivalence approaches to classify the telecom customers. Social position can be evaluated by finding the centrality of a node identified through a number of connections among network members. Such measures are used to characterize degrees of influence, prominence and importance of certain members. Regular equivalence analysis seeks to identify customers as churners and non-churners based on regularities in the patterns of network ties.