NDLI: DyadChurn: Customer Churn Prediction using Strong Social Ties

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DyadChurn: Customer Churn Prediction using Strong Social Ties

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DyadChurn: Customer Churn Prediction using Strong Social Ties

Content Provider	ACM Digital Library
Author	El-Beltagy, Samhaa R. Abd-Allah, Marwa N. Salah, Akram
Abstract	The increase in mobile phone subscriptions in recent years, has led to near market saturation in the telecom industry. As a result, it has become harder for telecom providers to acquire new customers, and the need for retaining existing ones has become of paramount importance. Because of fierce competition between different telecom providers and because the ease of which customers can move from one provider to another, all telecom service providers suffer from customer churn. In this paper, we propose a dyadic based churn prediction model, DyadChurn, where customer churn is modeled through social influence that propagates in the telecom network over strong social ties. We propose a novel method for evaluating social tie strength between telecom customers. We then, incorporate strong social ties in an influence propagation model to predict the set of future potential churners. The evaluation of the proposed dyadic based churn prediction model has been done using a real dataset, from one of the largest telecom companies in Egypt. The experimental results showed that the "length of calls" between customers is the most effective attribute in predicting social influence that result in churning. The results also showed that strong social ties (as opposed to weak ties) were the most effective ties in determining churn. Using strong social ties only enhanced the prediction accuracy (in terms of the lift curve) by more than 20%, when compared to a diffusion model.
Starting Page	253
Ending Page	263
Page Count	11
File Format	PDF
ISBN	9781450352208
DOI	10.1145/3105831.3105832
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-07-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Social network analysis Social tie strength Churn prediction
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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