Churn prediction in MMORPGs: A social influence based approach

Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009

Volumn 4, Issue , 2009, Pages 423-428

  Kawale, Jaya ^a   Pal, Aditya ^a   Srivastava, Jaideep ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVITY PATTERNS; CONVENTIONAL DIFFUSION MODEL; CURRENT ESTIMATES; CUSTOMERBASE; DATA SETS; DIFFUSION MODEL; MASSIVELY MULTIPLAYER; MMORPGS; NEGATIVE INFLUENCE; PREDICTION ACCURACY; PREDICTION MODEL; REVENUE POTENTIAL; ROLE-PLAYING GAME; SOCIAL INFLUENCE; SOCIAL NETWORK ANALYSIS; SOCIAL NETWORKS; SOCIAL TIES; STRUCTURE AND DYNAMICS; VECTOR QUANTITY; VIRTUAL WORLDS;

BEHAVIORAL RESEARCH; COMPUTER SCIENCE; ELECTRIC NETWORK ANALYSIS; MATHEMATICAL MODELS; VIRTUAL REALITY;

DIFFUSION;

EID: 70849098046     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSE.2009.80     Document Type: Conference Paper

References (15)

1. P. Datta, B. Masand, D. R. Mani, and B. Li, "Automated cellular modeling and prediction on a large scale, " Artif. Intell. Rev., vol. 14, no. 6, pp. 485-502, 2000.
2. J. Hadden, A. Tiwari, R. Roy, and D. Ruta, "Churn prediction using complaints data, " in Proceedings Of World Academy Of Science, Engineering and Technology.
3. K. Ng and H. Liu, "Customer retention via data mining, " Artif. Intell. Rev., vol. 14, no. 6, pp. 569-590, 2000.
4. W. Buckinx and D. V. D. Poel, "Customer base analysis: Partial defection of behaviorally-loyal clients in a non-contractual fmcg retail setting, " Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/178, Ghent University, Faculty of Economics and Business Administration, May 2003.
5. D. L. B. S. E. Jones, Michael A.; Mothersbaugh, "Switching barriers and repurchase intentions in services, " Journal of Retailing, 2000.
6. K. Morik and H. Köpcke, "Analysing customer churn in insurance data: a case study, " in PKDD '04: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, (New York, NY, USA), pp. 325-336, Springer-Verlag New York, Inc., 2004.
7. J. Lu, "Predicting customer churn in the telecommunications industry an application of survival analysis modeling using sas, ".
8. G. I. MariaMavri, "Customer switching behaviour in greek banking services using survival analysis, " Managerial Finance, vol. 34, pp. 186 - 197, 2008.
9. R. K. Gopal and S. K. Meher, "Customer churn time prediction in mobile telecommunication industry using ordinal regression, " in PAKDD, pp. 884-889, 2008.
10. "Customer churn prediction using improved one-class support vector machine, " vol. 3584/2005, pp. 300-306.
11. V. CoussementK, "Churn prediction in subscription services: An application of support vector machines while comparing two parameterselection techniques, " vol. 34(1), pp. 313-27, 2008.
12. T.-S. Lee, C.-C. Chiu, Y.-C. Chou, and C.-J. Lu, "Mining the customer credit using classification and regression tree and multivariate adaptive regression splines, " Computational Statistics and Data Analysis, vol. 50, pp. 1113-1130, February 2006.
13. K. Dasgupta, R. Singh, B. Viswanathan, D. Chakraborty, S. Mukherjea, A. A. Nanavati, and A. Joshi, "Social ties and their relevance to churn in mobile telecom networks, " in EDBT '08: Proceedings of the 11th international conference on Extending database technology, (New York, NY, USA), pp. 668-677, ACM, 2008.
14. S. Hill, F. Provost, and C. Volinsky, "Network-based marketing: Identifying likely adopters via consumer networks, " Statistical Science, vol. 22, no. 2, pp. 256-275, 2006.
15. S. R. Garner, "Weka: The waikato environment for knowledge analysis, " in In Proc. of the New Zealand Computer Science Research Students Conference, pp. 57-64, 1995.