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For: Challet-Bouju G, Hardouin JB, Thiabaud E, Saillard A, Donnio Y, Grall-Bronnec M, Perrot B. Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis. J Med Internet Res 2020;22:e17675. [PMID: 32254041 DOI: 10.2196/17675] [Cited by in Crossref: 11] [Cited by in F6Publishing: 12] [Article Influence: 3.7] [Reference Citation Analysis]
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1 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 2022. [DOI: 10.1080/14459795.2022.2135753] [Reference Citation Analysis]
2 Perrot B, Hardouin JB, 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. J Behav Addict 2022;11:874-89. [PMID: 36125924 DOI: 10.1556/2006.2022.00063] [Reference Citation Analysis]
3 Auer M, Griffiths MD. Attitude Towards Deposit Limits and Relationship with Their Account-Based Data Among a Sample of German Online Slots Players. J Gambl Stud 2022. [PMID: 36002706 DOI: 10.1007/s10899-022-10155-1] [Reference Citation Analysis]
4 Hopfgartner N, Auer M, Griffiths MD, Helic D. Predicting self-exclusion among online gamblers: An empirical real-world study. J Gambl Stud 2022. [PMID: 35947331 DOI: 10.1007/s10899-022-10149-z] [Reference Citation Analysis]
5 Auer M, Griffiths MD. Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting. J Gambl Stud. [DOI: 10.1007/s10899-022-10139-1] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Balem M, Perrot B, Hardouin JB, 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;117:1020-34. [PMID: 34374151 DOI: 10.1111/add.15665] [Reference Citation Analysis]
7 Whiteford S, Hoon AE, 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. [DOI: 10.1016/j.chbr.2022.100194] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Xi R, Gao B, Xia X. Real-time Feedback System of Funding Data Flow Based on Data Tracking and Classification. 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) 2021. [DOI: 10.1109/i-smac52330.2021.9640661] [Reference Citation Analysis]
9 Chagas BT, Gomes JFS, Griffiths MD. Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery. J Gambl Stud 2021. [PMID: 34518986 DOI: 10.1007/s10899-021-10072-9] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
10 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. J Med Internet Res 2021;23:e24088. [PMID: 34152282 DOI: 10.2196/24088] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]