Abstract
In this paper we address the problem of churning in the telecommunication sector in Indian context. Churning becomes a challenging problem for telecom industries especially when the subscriber base almost reaches saturation level. It directly affect the revenue of the telecom companies. A proper analysis of factors affecting churning can help the telecom service providers to reduce churning, satisfy their customers and may be design new products to reduce churning. We use social media analytics, in particular twitter feeds, to get opinion of the users. The main contribution of the paper is feasibility of data mining tools, in particular association rules, to determine factors affecting churning.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
References
Agrawal, R., Imieliski, T., Swami, A.: Mining association rules between sets of items in large databases. ACM SIGMOD Record 22(2), 207–216 (1993)
Cheung, K.W., Kwok, J.T., Law, M.H., Tsui, K.C.: Mining customer product ratings for personalized marketing. Decision Support Systems 35, 231–243 (2003)
Fournier-Viger, P., Wu, C.-W., Tseng, V.S.: Mining top-k association rules. In: Kosseim, L., Inkpen, D. (eds.) Canadian AI 2012. LNCS, vol. 7310, pp. 61–73. Springer, Heidelberg (2012)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM (2004)
Hung, S.Y., Yen, D.C., Wang, H.Y.: Applying data mining to telecom churn management. Expert Systems with Applications 31(3), 515–524 (2006)
Hwang, H., Jung, T., Suh, E.: An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry. Expert Systems with Applications 26(2), 181–188 (2004)
Keaveney, S.M.: Customer switching behavior in service industries: An exploratory study. Journal of Marketing 59(2), 71–82 (1995)
Kim, H.S., Yoon, C.H.: Determinants of subscriber churn and customer loyalty in the Korean mobile telephony market. Telecommunications Policy 28(9/10), 751–765 (2004)
Kim, S.Y., Jung, T.S., Suh, E.H., Hwang, H.S.: Customer segmentation and strategy development based on customer lifetime value: A case study. Expert Systems with Applications 31, 101–107 (2006)
Norvig, P.: How to write a spelling corrector, http://norvig.com/spell-correct.html (visited February 8, 2013)
Oghojafor, B., et al.: Discriminant Analysis of Factors Affecting Telecoms Customer Churn. International Journal of Business Administration 3(2) (2012)
Taboada, M., et al.: Lexicon-based methods for sentiment analysis. Computational Linguistics 37(2), 267–307 (2011)
Telecom Regulatory Authority of India, Telecom Subscription Data as on 30th September, Press Release No. 78/2013
Telecommunications in India, In Wikipedia, http://en.wikipedia.org/wiki/Telecommunications_in_India (retrieved January 24, 2014)
Wei, C.P., Chiu, I.T.: Turning telecommunications call details to churn prediction: A data mining approach. Expert Systems with Applications 23(2), 103–112 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Varshney, N., Gupta, S.K. (2014). Mining Churning Factors in Indian Telecommunication Sector Using Social Media Analytics. In: Bellatreche, L., Mohania, M.K. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2014. Lecture Notes in Computer Science, vol 8646. Springer, Cham. https://doi.org/10.1007/978-3-319-10160-6_36
Download citation
DOI: https://doi.org/10.1007/978-3-319-10160-6_36
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10159-0
Online ISBN: 978-3-319-10160-6
eBook Packages: Computer ScienceComputer Science (R0)