A New Framework for Churners’ Influence Analysis Using Call Data Records

Abstract

Predicting customer churn is of paramount importance in telecommunication companies. The taxonomy of churn reports that, not only individual constraints but also social factors can create users’ propensity to churn. This study uses real world call data records (CDR) to extract the social relationships among mobile phone users and build a multi relational social network, where the influence of users diffuses. The research is conducted to propose a framework that enhances the actionable value of social influence of predicted churners and to examine the parameters that control the churn information diffusion in the telecommunication networks.