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Inside the Decentralised Casino: a longitudinal study of actual cryptocurrency gambling transactions

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Author(s): Scholten, Oliver J. ; Walker, James A. ; Zendle, David

Publisher: Open Science Framework

Year Published: 2020

Date Added: December 22, 2020

This dataset accompanies a study of the same title published in PLOS One. It offers a list of publicly available gambling related transactions derived from the Ethereum blockchain. This data includes over 2.2M individual transactions across 24,000+ unique addresses from three decentralised gambling applications over 583 days. It also includes calculated behavioural measures for each player found in each application. The study explored spending behaviours in decentralised gambling applications. It found that the average player spent less than in other online casinos, but heavily involved player spent much more. Because these applications use cryptocurrencies, the transactions are publicly available. Thus, this data can be used in academic research, including large scale data analysis.

The study published in PLOS One can be viewed here.


Citation: Scholten, O. J., Walker, J. A., & Zendle, D. (2020). Inside the Decentralised Casino: a longitudinal study of actual cryptocurrency gambling transactions. Open Science Framework. Available from: https://doi.org/10.17605/OSF.IO/8BFYJ

DOI: https://doi.org/10.17605/OSF.IO/8BFYJ

Keywords: blockchain ; casino gambling ; casinos ; cryptocurrency ; gambling expenditures ; online gaming ; player tracking

Topics: Information for Operators ; Online Gambling ; Venue/Casino

Conceptual Framework Factors:   Gambling Types ; Exposure - Gambling Setting ; Types - Structural Characteristics ; Exposure - Accessibility ; Gambling Exposure

Geographic Coverage: Worldwide

Study Population: Online gamblers using three popular services for gambling with the Ethereum cryptocurrency

Sample Size: N = 2,232,741 transactions; N = 24,234 unique user addresses

Related Resources:
  • Exploring gambling using cryptocurrency on decentralized casinos

Study Funding:

This work was supported by the EPSRC Centre for Doctoral Training in Intelligent Games & Games Intelligence (IGGI) [EP/L015846/1] (OJS, PhD Scholarship) and the Digital Creativity Labs (digitalcreativity.ac.uk) (JAW, Research Fellow), jointly funded by EPSRC/AHRC/Innovate UK under grant no. EP/M023265/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Declaration:

The authors declare no actual or potential conflict of interest in relation to the preparation of this dataset and the related data paper.

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