Big Data and Information Analytics (BDIA)

Identifying electronic gaming machine gambling personae through unsupervised session classification
Pages: 141 - 175, Issue 2, April 2017

doi:10.3934/bdia.2017015      Abstract        References        Full text (1004.1K)           Related Articles

Maria Gabriella Mosquera - Faculty of Computer Science, Dalhousie University, 6050 University Avenue, Halifax, NS B3H 4R2, Canada (email)
Vlado Keselj - Faculty of Computer Science, Dalhousie University, 6050 University Avenue, Halifax, NS B3H 4R2, Canada (email)

1 C. C. Aggarwal, Outlier Analysis, Springer, New York, 2013.       
2 American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, $4^{th}$ edition, American Psychiatric Association, Washington, DC, 1994.
3 G. Banks, R. Fitzgerald and L. Sylvan, Gambling: Productivity Commission Inquiry Report, Technical Report 50, 2010, http://www.pc.gov.au/inquiries/completed/gambling-2009/report/gambling-report-volume1.pdf(visited on: 09/12/2012).
4 M. Berry and G. Linoff, Data Mining Techniques for Marketing, Sales, and Customer Relationship Management, $2^{nd}$ edition, Wiley Publishing Inc., Indianapolis, 2004.
5 J. Braverman, R. A. LaBrie and H. J. Shaffer, A taxometric analysis of actual Internet sport gambling behavior, Psychological Assessment, 23 (2011), 234-244.
6 J. Braverman, D. A. LaPlante, S. E. Nelson and H. J. Shaffer, Using cross-game behavioral markers for early identification of high-risk Internet gamblers, Psychology of Addictive Behaviors, 27 (2013), 868-877.
7 J. Braverman and H. J. Shaffer, How do gamblers start gambling: Identifying behavioral markers for high-risk Internet gambling, European Journal of Public Health, 22 (2012), 273-278.
8 S. Carpendale, Evaluating information visualizations, in Information Visualization, Lecture Notes in Computer Science, A simple univariate outlier identification procedure, 4950 (2008), 19-45.
9 National Research Council, Pathological Gambling: A Critical Review, National Academies Press, Washington, DC, 1999.
10 P. Delfabbro, A. Osborn, M. Nevile, L. Skelt and J. MacMillen, Identifying Problem Gamblers in Gambling Venues, Technical report, 2007.
11 M. J. Dixon, K. A. Harrigan, M. Jarrick, V. MacLaren, J. A. Fugelsang and E. Sheepy, Psychophysiological arousal signatures of near-misses in slot machine play, International Gambling Studies, 11 (2011), 393-407.
12 L. Dixon, R. Trigg and M. Griffiths, An empirical investigation of music and gambling behaviour, International Gambling Studies, 7 (2007), 315-326.
13 S. Dragicevic, G. Tsogas and A. Kudic, Analysis of casino online gambling data in relation to behavioural risk markers for high-risk gambling and player protection, International Gambling Studies, 11 (2011), 377-391.
14 M. Ellery, S. H. Stewart and P. Loba, Alcohol's effects on video lottery terminal (vlt) play among probable pathological and non-pathological gamblers, Journal of Gambling Studies, 21 (2005), 299-324.
15 J. Ferris and H. Wynne, The Canadian Problem Gambling Index: Final Report, Technical Report, 2001, http://www.ccgr.ca/en/projects/resources/CPGI-Final-Report-English.pdf(visited on: 06/28/2013).
16 G. Data, Canadian Gaming Market Report, Technical report, 2011, http://www.gamblingdata.com/files/Gambling%20Data%20Canadian%20Gaming%20Market%20Report%20Final_0.pdf (visited on: 04/10/2013).
17 GSA, G2S Message Protocol v1.1 Game-to-system, Technical Report GSA-P0075.024.00-2011, GSA, 2011.
18 GSA, G2S Message Protocol v2.0 Game-to-system, Technical Report GSA-P0075.0800.00-2006, GSA, 2006.
19 J. Han and M. Kamber, Data Mining: Concepts and Techniques, $3^{rd}$ edition, Morgan Kaufmann, Waltham, 2012.
20 K. A. Harrigan and M. Dixon, Par sheets, probabilities, and slot machine play: Implications of problem and non-problem gambling, Journal of Gambling Issues, 23 (2009), 81-110.
21 K. A. Harrigan, Slot machine structural characteristics: Distorted player views of payback percentages, Journal of Gambling Issues, 20 (2007), 215-234.
22 K. A. Harrigan, Slot machines: Pursuing responsible gaming practices for virtual reels and near misses, International Journal of Mental Health Addiction, 7 (2009), 68-83.
23 C. Hennig, Cluster-wise assessment of cluster stability, Computational Statistics & Data Analysis, 52 (2007), 258-271.       
24 D. C. Hoaglin, John W. Tukey and data analysis, Statistical Science, 18 (2003), 311-318.       
25 B. Iglewicz and S. Banerjee, A Simple Univariate Outlier Identification Procedure, Proceedings of Annual Meeting of the American Statistical Association, 2001.
26 R. A. LaBrie, D. A. LaPlante, S. E. Nelson, A. Schumann and H. J. Shaffer, Assessing the playing field: A prospective longitudinal study of Internet sports gambling behavior, Journal of Gambling Studies, 23 (2007), 347-362.
27 R. A. LaBrie, S. A. Kaplan, D. A. LaPlante, S. E. Nelson and H. J. Shaffer, Inside the virtual casino: A prospective longitudinal study of actual Internet casino gambling, European Journal of Public Health, 18 (2008), 410-416.
28 D. A. LaPlante, S. E. Nelson, R. A. LaBrie and H. J. Shaffer, Stability and progression of disordered gambling: Lessons from longitudinal studies, Canadian Journal of Psychiatry, 53 (2008), 52-60.
29 D. A. LaPlante, S. E. Nelson, R. A. LaBrie and H. J. Shaffer, Disordered gambling, type of gambling and gambling involvement in the British gambling prevalence survey 2007, European Journal of Public Health, 21 (2011), 532-537.
30 H. Liu and V. Keselj, Combined mining of web server logs and web contents for classifying user navigation patterns and predicting users' future requests, Data & Knowledge Engineering, 61 (2007), 304-330.
31 P. Loba, S. H. Stewart, R. M. Klein and J. R. Blackburn, Manipulations of the features of standard video lottery terminal (VLT) games: Effects in pathological and non-pathological gamblers, Journal of Gambling Studies, 17 (2001), 94-98.
32 V. V. MacLaren, J. A. Fugelsang, K. Harrigan and M. Dixon, The personality of pathological gamblers: A meta-analysis, Clinical Psychology Review, 31 (2011), 1057-1067.
33 K. Marshall, Gambling 2011, Technical Report 4, 2011, http://www.statcan.gc.ca/pub/75-001-x/2011004/article/11551-eng.pdf(visited on: 04/10/2013).
34 S. Mishra, M. L. Lumiére and R. J. Williams, Gambling as a form of risk-taking: Individual differences in personality, risk-accepting attitudes, and behavioral preferences for risk, Personality and Individual Differences, 49 (2010), 616-621.
35 National Research Council, Pathological Gambling: A Critical Review, The National Academies Press, Washington D.C., 1999.
36 S. R. Nelson, D. A. LaPlante, A. J. Peller, A. Schumann, R. A. LaBrie and H. J. Shaffer, Real limits in the virtual world: Self-limiting behavior of Internet gamblers, Journal of Gambling Studies, 24 (2008), 463-477.
37 J. Pallant, SPSS Survival Manual: A Step By Step Guide to Data Analysis Using SPSS, $4^{th}$ edition, Allen & Unwin, Sydney, 2011.
38 Y. Peng, K. Gang and Y. Shi (eds.), Knowledge-rich data mining in financial risk detection, in Computational Science - ICCS 2009 (eds. G. Allen, J. Nabrzyski, E. Seidel, G. D. van Albada, J. Dongarra and P. M. A. Sloot), Springer Berlin Heidelberg, 5545 (2009), 534-542.
39 D. T. Pham, S. S. Dimov and C. D. Nguyen, Selection of k in k-means clustering, Journal of Mechanical Engineering Science, 219 (2005), 103-119.
40 A. Rakhlin and A. Caponnetto (eds.), Stability of k-means clustering, in Advances in Neural Information Processing Systems 19 (eds. B. Schölkopf, J. Platt and T. Hoffman), MIT Press, (2006), 1121-1128. http://papers.nips.cc/paper/3116-stability-of-k-means-clustering (visited on: 12/10/2014)
41 Responsible Gambling Council, Electronic Gaming Machines and Problem Gambling, Saskachewan Liquour and Gaming Authority, 2006, http://www.responsiblegambling.org/docs/research-reports/electronic-gaming-machines-and-problem-gambling.pdf?sfvrsn=10 (visited on: 06/28/2013).
42 Responsible Gambling Council, Canadian Gambling Digest 2011-2012, Technical report, 2013, (visited on: 05/04/2015).
43 G. Schwartz, The Impulse Economy, Atria Books, New York, 2011.
44 S. Seo, A Review and Comparison of Methods for Detecting Outliers in Univariate Data Sets, M.S thesis, University of Pittsburg in Pensylvania, 2006.
45 H. J. Shaffer and D. A. Korn, Gambling and related mental disorders: A public health analysis, Annual Review of Public Health, 23 (2002), 171-212.
46 H. J. Shaffer, A. J. Peller, D. A. LaPlante, S. E. Nelson and R. A. LaBrie, Toward a paradigm shift in Internet gambling research: From opinion and self-report to actual behavior, Addiction Research and Theory, 18 (2010), 270-283.
47 J. Sim and C. C. Wright, Understanding interobserver agreement: The Kappa statistic, Family Medicine, 37 (2005), 360-363.
48 S. H. Stewart, P. Collins, J. R. Blackburn, M. Ellery and R. M. Klein, Heart rate increase to alcohol administration and video lottery terminal (VLT) play among regular VLT players, Psychology of Addictive Behaviors, 19 (2005), 94-98.
49 S. Tufféry, Data Mining and Statistics for Decision Making, John Wiley & Sons, Ltd., Chichester, 2011.
50 A. J. Viera and J. M. Garrett, The Kappa statistic in reliability studies: Use, interpretation, and sample size requirements, Journal of the American Physical Therapy Association, 85 (2005), 257-268.
51 C. Wheelan, Naked Statistics: Stripping the Dread from the Data, W.W. Norton and Company, New York, 2013.
52 R. J. Williams, R. A. Volberg and R. M. G. Stevens, The Population Prevalence of Problem Gambling: Methodological Influences, Standardized Rates, Jurisdictional Differences, and Worldwide Trends, Technical report, 2012, http://www.uleth.ca/dspace/bitstream/handle/10133/3068/2012-PREVALENCE-OPGRC%20(2).pdf?sequence=3 (visited on: 08/12/2013).
53 D. S. Wilson, R. A. Kauffman and M. S. Purdy, A program for at-risk high school students informed by evolutionary science, PLoS ONE, 6 (2011), e27826.
54 I. H. Witten and E. Frank, Data mining: Practical machine learning tools and techniques, Newsletter: ACM SIGMOD Record Homepage archive, 31 (2002), 76-77.
55 Z. Xuan and H. Shaffer, How do gamblers end gambling: Longitudinal analysis of Internet gambling behaviors prior to account closure due to gambling related problems, Journal of Gambling Studies, 25 (2009), 239-252.

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