Application of Social Network Inferred Data to Churn Modeling in Telecoms
The subject of this work is the use of social network analysis to increase the effectiveness of methods used to predict churn of telephony network subscribers. The social network is created on the basis of operational data (CDR records). The result of the analysis is customer segmentation and additi...
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| Published in | Journal of Telecommunications and Information Technology Vol. 2; no. 2016; pp. 77 - 86 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Warsaw
Instytut Lacznosci - Panstwowy Instytut Badawczy (National Institute of Telecommunications)
30.06.2016
National Institute of Telecommunications |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1509-4553 1899-8852 |
| DOI | 10.26636/jtit.2016.2.722 |
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| Abstract | The subject of this work is the use of social network analysis to increase the effectiveness of methods used to predict churn of telephony network subscribers. The social network is created on the basis of operational data (CDR records). The result of the analysis is customer segmentation and additional predictor variables. Proposed hybrid predictor employs set of regression models tuned to specific customer segments. The verification was performed on data obtained from one of the Polish operators. |
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| AbstractList | The subject of this work is the use of social network analysis to increase the effectiveness of methods used to predict churn of telephony network subscribers. The social network is created on the basis of operational data (CDR records). The result of the analysis is customer segmentation and additional predictor variables. Proposed hybrid predictor employs set of regression models tuned to specific customer segments. The verification was performed on data obtained from one of the Polish operators. |
| Author | Gruszczyński, Witold |
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| Cites_doi | 10.1126/science.286.5439.509 10.1137/1.9781611972801.64 10.1016/j.asoc.2013.09.017 10.1016/j.telpol.2004.05.013 10.1145/335305.335326 10.1007/978-3-642-15246-7_67 10.1109/cason.2011.6085932 10.1145/2527031.2527051 10.1145/1352431.1352512 10.1103/PhysRevE.69.026113 10.1007/978-3-642-13529-3_74 10.1109/cason.2011.6085947 10.1145/2665994.2665997 10.1007/978-3-642-22000-5_8 |
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| SubjectTerms | churn reduction classification Information technology Mathematical models Regression Regression analysis Segmentation Segments Social networks Telecommunications |
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| Title | Application of Social Network Inferred Data to Churn Modeling in Telecoms |
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