Communications-based early detection of gambling-related problems in online gambling

Abstract

Most algorithms developed for the early identification of gambling-related problems rely on predictors aggregated out of transactional gambling data. However, as a notable extension, one algorithm uses predictors derived from written correspondence with players and thereby opens up a so far unused resource for the early detection of gambling-related problems. In this article, a sample of 1008 emails from self-excluders and controls to the customer services of an online gambling operator was reanalysed to explore the possibility of using automated text analysis software to extract quantitative markers from written player correspondence. For this purpose a text analysis tool, using psychometrically validated English and German dictionaries, was applied. While the classification results that were based solely on automated text analysis were nearly on a level with those attained by human assessment, the application of an automated prediction model can even add incremental validity to human judgements. A combined model, relying on human rating as well as the scales Anger, Time and Causation, derived from automated text analysis, displayed improved validity and classification rate. Discussed in the light of practical application, the results indicate that automated text analysis can be deployed as an expert system to prioritize cases and to support human judgement.

Keywords::

• responsible gambling
• harm minimization
• Internet
• prediction
• text analysis

Acknowledgements

This study was not supported by grant funding.

Conflicts of interest

The co-author Joachim Haeusler is a full-time employee of bwin.party digital entertainment plc, which offers online gambling products.

Additional information

Notes on contributors

Joerg Haefeli

Joerg Haefeli has been a lecturer and project manager at the University of Applied Sciences and Arts – Social Work (HSLU) since 1998. He is a social worker and academic organization developer (MAS). His main interests in teaching and research are in the area of prevention and early detection of (gambling) addiction and other societal problem areas.

Suzanne Lischer

Suzanne Lischer has been a lecturer and project manager at the University of Applied Sciences and Arts – Social Work (HSLU) since 2011. She holds a doctorate in media sciences (FU Berlin) and a masters in social sciences, and she is also qualified as graduate social worker. Her main focus in teaching and research is in the area of harm reduction in the gambling field and other societal problem areas.

Joachim Haeusler

Joachim Haeusler holds a masters in psychology and has acted as head of corporate responsibility for bwin.party digital entertainment plc since 2008. In this function, he is responsible for the strategic development and innovation of player protection tools and policies.