Document Type
Conference Proceeding
Publication Date
11-9-2012
Abstract
The saturation of mobile phone markets has resulted in rising costs for operators to obtain new customers. These operators thus focus their energies on identifying users that will churn so they can be targeted for retention campaigns. Typical churn prediction algorithms identify churners based on service usage metrics, network performance indicators, and demographic information. Social and peer-influence to churn, however, is usually not considered. In this paper, we describe a new churn prediction algorithm that incorporates the influence churners spread to their social peers. Using data from a major service provider, we show that social influence improves churn prediction and is among the most important factors.
Repository Citation
Doran, D.,
Mendiratta, V.,
Phadke, C.,
Kushnir, D.,
& Uzunalioglu, H.
(2012). Using Social Influence to Predict Subscriber Churn. .
https://corescholar.libraries.wright.edu/knoesis/1050
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Poster presented at the Interdisciplinary Workshop on Information and Decision in Social Networks, Cambridge, MA, November 8-9, 2012.