A Governmentality of Online Gambling: Quebec’s Contested Internet Gambling Website Blocking Provisions

This article examines Canada’s first internet gambling website blocking scheme, which was enacted in Quebec as part of the implementation of the province’s 2015 budget. Using qualitative research methods, the article illustrates the complexities of regulating online gambling. Influenced by critical sociological and anthropological studies of gambling, and taking a socio-legal, governmentality perspective, it shows how socio-legal studies can illuminate research on the regulation of gambling, and how the study of online gambling can, as a sentinel site for the regulation of online consumption, contribute to the development of socio-legal studies. Our analysis shows that the governmentality of online gambling is framed so as to exclude 1) a range of risks (e.g., related to consumer profiling and the capacity to stimulate “addictive consumption”), 2) the heterogeneity of everyday experience that connects online gambling with online addictive consumption more generally, and 3) a range of possibilities for governing online gambling otherwise.

Detecting Anomalous Transactions via an IoT Based Application: A Machine Learning Approach for Horse Racing Betting

During the past decade, the technological advancement have allowed the gambling industry worldwide to deploy various platforms such as the web and mobile applications. Government agencies and local authorities have place strict regulations regarding the location and amount allowed for gambling. These efforts are made to prevent gambling addictions and monitor fraudulent activities. The revenue earned from gambling provides a considerable amount of tax revenue. The inception of internet gambling have allowed professional gamblers to par take in unlawful acts. However, the lack of studies on the technical inspections and systems to prohibit unlawful internet gambling has caused incidents such as the Walkerhill Hotel incident in 2016, where fraudsters placed bets abnormally by modifying an Internet of Things (IoT)-based application called “MyCard”. This paper investigates the logic used by smartphone IoT applications to validate the location of users and then confirm continuous threats. Hence, our research analyzed transactions made on applications that operated using location authentication through IoT devices. Drawing on gambling transaction data from the Korea Racing Authority, this research used time series machine learning algorithms to identify anomalous activities and transactions. In our research, we propose a method to detect and prevent these anomalies by conducting a comparative analysis of the results of existing anomaly detection techniques and novel techniques.

Reducing Internet Gambling Harms Using Behavioral Science: A Stakeholder Framework

Internet gambling provides a unique environment with design mechanics and data-driven opportunities that can impact gambling-related harms. Some elements of Internet gambling including isolation, lack of interruption, and constant, easy access have been argued to pose specific risks. However, identifiable player accounts enable identification of behavioral risk markers and personalized private interfaces to push customized messages and interventions. The structural design of the Internet gambling environment (website or app) can have a strong influence on individual behavior. However, unlike land-based venues, Internet gambling has few specific policies outlining acceptable and unacceptable design practices. Harm minimization including responsible gambling frameworks typically include roles and responsibilities for multiple stakeholders including individual users, industry operators, government regulators, and community organizations. This paper presents a framework for how behavioral science principles can inform appropriate stakeholder actions to minimize Internet gambling-related harms. A customer journey through internet gambling demonstrates how a multidisciplinary nexus of collaborative effort may facilitate a reduction in harms associated with Internet gambling for consumers at all stages of risk. Collaborative efforts between stakeholders could result in the implementation of appropriate design strategies to assist individuals to make decisions and engage in healthy, sustainable behaviors.

Technology, the Internet, and Gambling

Many people worry that exposure to Internet gambling will overpower individuals’ self-control, stimulate addictive behavior patterns, and provide the context to sustain addiction once it emerges. Though many researchers have attempted to evaluate this proposition, they have been limited by their methodological approaches—specifically, their use of convenience samples and self-reports of Internet gambling behavior. At the Division on Addiction, the authors collaborated with bwin.party digital entertainment to examine electronically recorded gambling data (i.e., records of actual gambling) among bwin.party subscribers. As described in this chapter, their early epidemiological studies revealed that few Internet gamblers are intemperate and that the typical Internet player gambles moderately. However, those who do use the Internet to gamble excessively often experience lasting and far-reaching harm. The authors review prevention and intervention strategies to help promote healthier Internet gambling. These cross-cutting strategies emerge from public policy, public health, corporate social responsibility, and other fields. With regard to user-initiated strategies, the authors describe what researchers have discovered about the effectiveness and reach of self-limitation and self-exclusion programs. With regard to operator-initiated strategies, they propose a series of steps leading to the development of algorithms designed to predict which Internet gamblers will require interventions to reduce gambling harm. The authors describe their approach to these steps during their work developing predictive algorithms for bwin.party. Finally, the chapter considers ethical principles that should inform the development of programs and policies designed to provide the safest possible Internet gambling experience.

The erosion of nongambling spheres by smartphone gambling: A qualitative study on workplace and domestic disordered gambling

The potential dangers of internet-based gambling as compared with more traditional land-based gambling have been increasingly investigated over the past decade. The general consensus appears to be that although internet gambling might not be a more dangerous medium for gambling per se, the 24/7 availability it generates for problem gamblers, however, is. Because smartphones have become the most used way of gambling online, internet gambling must, therefore, be further subcategorized according to the device by which it is accessed. This study examines the issue by exploring the views of smartphone gamblers undergoing treatment for gambling disorder in focus group settings ( N=35). Utilizing thematic analysis, the paper shows that smartphone gambling has colonized spaces previously regarded as nongambling spheres. The workplace, especially in male-dominated contexts, emerged as an accommodator and stimulator of gambling behavior, raising issues of productivity rather than criminality. Domestic gambling was mostly characterized by an invasion of bathroom and bedtime spheres of intimacy. The study examines the implications of prevention and treatment, focusing on the minimization of exposure to gambling stimuli, the erosion of intimacy that recovering gamblers must endure, and the necessity of embracing a broader definition of gambling-related harm.

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

Background Individuals who gamble online may be at risk of gambling excessively, but internet gambling also provides a unique opportunity to monitor gambling behavior in real environments which may allow intervention for those who encounter difficulties. Objective The objective of this study was to model the early gambling trajectories of individuals who play online lottery. Methods Anonymized gambling‐related records of the initial 6 months of 1152 clients of the French national lottery who created their internet gambling accounts between September 2015 and February 2016 were analyzed using a two-step approach that combined growth mixture modeling and latent class analysis. The analysis was based upon behavior indicators of gambling activity (money wagered and number of gambling days) and indicators of gambling problems (breadth of involvement and chasing). Profiles were described based upon the probabilities of following the trajectories that were identified for the four indicators, and upon several covariates (age, gender, deposits, type of play, net losses, voluntary self-exclusion, and Playscan classification—a responsible gambling tool that provides each player with a risk assessment: green for low risk, orange for medium risk and red for high risk). Net losses, voluntary self-exclusion, and Playscan classification were used as external verification of problem gambling. Results We identified 5 distinct profiles of online lottery gambling. Classes 1 (56.8%), 2 (14.8%) and 3 (13.9%) were characterized by low to medium gambling activity and low values for markers of problem gambling. They displayed low net losses, did not use the voluntary self-exclusion measure, and were classified predominantly with green Playscan tags (range 90%-98%). Class 4 (9.7%) was characterized by medium to high gambling activity, played a higher breadth of game types (range 1-6), and had zero to few chasing episodes. They had high net losses but were classified with green (66%) or orange (25%) Playscan tags and did not use the voluntary self-exclusion measure. Class 5 (4.8%) was characterized by medium to very high gambling activity, played a higher breadth of game types (range 1-17), and had a high number of chasing episodes (range 0-5). They experienced the highest net losses, the highest proportion of orange (32%) and red (39%) tags within the Playscan classification system and represented the only class in which voluntary self-exclusion was present. Conclusions Classes 1, 2, 3 may be considered to represent recreational gambling. Class 4 had higher gambling activity and higher breadth of involvement and may be representative of players at risk for future gambling problems. Class 5 stood out in terms of much higher gambling activity and breadth of involvement, and the presence of chasing behavior. Individuals in classes 4 and 5 may benefit from early preventive measures.