Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17675, first published .
Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis

Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis

Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis

Journals

  1. Yokotani K. A Change Talk Model for Abstinence Based on Web-Based Anonymous Gambler Chat Meeting Data by Using an Automatic Change Talk Classifier: Development Study. Journal of Medical Internet Research 2021;23(6):e24088 View
  2. Auer M, Griffiths M. The Effect of a Mandatory Play Break on Subsequent Gambling Behavior among British Online Casino Players: A Large-Scale Real-World Study. Journal of Gambling Studies 2022;39(1):383 View
  3. Perrot B, Hardouin J, Thiabaud E, Saillard A, Grall-Bronnec M, Challet-Bouju G. Development and validation of a prediction model for online gambling problems based on players' account data. Journal of Behavioral Addictions 2022;11(3):874 View
  4. Auer M, Griffiths M. An Empirical Attempt to Operationalize Chasing Losses in Gambling Utilizing Account-Based Player Tracking Data. Journal of Gambling Studies 2022;39(4):1547 View
  5. Chagas B, Gomes J, Griffiths M. Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery. Journal of Gambling Studies 2021;38(3):917 View
  6. Whiteford S, Hoon A, James R, Tunney R, Dymond S. Quantile regression analysis of in-play betting in a large online gambling dataset. Computers in Human Behavior Reports 2022;6:100194 View
  7. Ghaharian K, Abarbanel B, Phung D, Puranik P, Kraus S, Feldman A, Bernhard B. Applications of data science for responsible gambling: a scoping review. International Gambling Studies 2023;23(2):289 View
  8. Balem M, Perrot B, Hardouin J, Thiabaud E, Saillard A, Grall‐Bronnec M, Challet‐Bouju G. Impact of wagering inducements on the gambling behaviors of on‐line gamblers: A longitudinal study based on gambling tracking data. Addiction 2022;117(4):1020 View
  9. Auer M, Griffiths M. Attitude Towards Deposit Limits and Relationship with Their Account-Based Data Among a Sample of German Online Slots Players. Journal of Gambling Studies 2022;39(3):1319 View
  10. Ghaharian K, Abarbanel B, Kraus S, Singh A, Bernhard B. Players Gonna Pay: Characterizing gamblers and gambling-related harm with payments transaction data. Computers in Human Behavior 2023;143:107717 View
  11. Auer M, Griffiths M. Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting. Journal of Gambling Studies 2022;39(3):1273 View
  12. Hopfgartner N, Auer M, Griffiths M, Helic D. Predicting self-exclusion among online gamblers: An empirical real-world study. Journal of Gambling Studies 2022;39(1):447 View
  13. Ghaharian K, Puranik P, Abarbanel B, Taghva K, Kraus S, Singh A, Feldman A, Bernhard B. Payments transaction data from online casino players and online sports bettors. Data in Brief 2023;48:109077 View
  14. Delfabbro P, Parke J, Catania M, Chikh K. Behavioural Markers of Harm and Their Potential in Identifying Product Risk in Online Gambling. International Journal of Mental Health and Addiction 2023 View
  15. Auer M, Griffiths M. Predicting High-Risk Gambling Based on the First Seven Days of Gambling Activity After Registration Using Account-Based Tracking Data. International Journal of Mental Health and Addiction 2023 View
  16. Auer M, Griffiths M. An empirical attempt to identify binge gambling utilizing account-based player tracking data. Addiction Research & Theory 2024;32(4):264 View
  17. Ghaharian K, Abarbanel B, Kraus S, Singh A, Bernhard B. Evaluating the generalizability of payment behavioral profiles across gambling brands. International Gambling Studies 2024;24(1):152 View
  18. Delfabbro P, Parke J, Catania M. Behavioural Tracking and Profiling Studies Involving Objective Data Derived from Online Operators: A Review of the Evidence. Journal of Gambling Studies 2023;40(2):639 View
  19. Auer M, Ricijas N, Kranzelic V, Griffiths M. Development of the Online Problem Gaming Behavior Index: A New Scale Based on Actual Problem Gambling Behavior Rather Than the Consequences of it. Evaluation & the Health Professions 2024;47(1):81 View
  20. Banerjee N, Chen Z, Clark L, Noël X. Behavioural expressions of loss-chasing in gambling: A systematic scoping review. Neuroscience & Biobehavioral Reviews 2023;153:105377 View
  21. Edson T, Louderback E, Tom M, McCullock S, LaPlante D. Exploring a multidimensional concept of loss chasing using online sports betting records. International Gambling Studies 2024;24(2):306 View
  22. Nelson S, Louderback E, Edson T, Tom M, LaPlante D. Overtime: Long-Term Betting Trajectories Among Highly-Involved and Less-Involved Online Sports Bettors. Journal of Gambling Studies 2024;40(3):1245 View
  23. Zhang K, Rights J, Deng X, Lesch T, Clark L. Within-session chasing of losses and wins in an online eCasino. Scientific Reports 2024;14(1) View
  24. Stechschulte G, Wintner M, Hemmje M, Schwarz J, Lischer S, Kaufmann M. In-Database Feature Extraction to Improve Early Detection of Problematic Online Gambling Behavior. IEEE Transactions on Computational Social Systems 2024;11(5):6868 View