The Potential for Serious Spaceships to Make a Serious Difference
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Fleet, Robert
Nurmikko-Fuller, Terhi
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Association for Computing Machinery (ACM)
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Identifying, investigating, and potentially disrupting organised criminal networks is difficult. Data gathered by law enforcement and regulatory authorities are often inconsistent, incomplete, and inaccurate. Computational criminology attempts to address these limitations by modelling the behaviour of virtual ?humans" in virtual places. However, virtual humans are rule-based and can never fully replicate actual human behaviour. This study takes a new approach by utilising the benefits of the observable and controllable environment of virtual worlds but examining real people and real behaviour. To do this, it explores real people's behaviour in a virtual environment similar to the circumstances found in organised criminal networks. Massively Multiplayer Online (MMO) video games with player-driven markets present real humans with similar circumstances in controlled and observable virtual environments. Market conditions within MMO games and illicit markets are both characterised by trust, reputation and, when all else fails, violence. Overall, MMO games are a novel data source to identify, investigate, and provide prevention strategies to the problem of organised criminal networks. Using social network analysis of real-world players from data broadcast by EVE Online (an MMO); spatial, temporal, and behavioural patterns of both offenders and victims are examined. The data broadcast from the game is consistent, complete, and accurate and provides a much larger sample size than obtainable in real-world environments. The data set consists of a seven-year period containing approximately 7M-9M events. It captures the activities of ~600,000 individuals and ~2,500 groups. This paper proposes that video games can approximate the circumstances found in the real world and human agents can and do act in the most rational way to maximise success in those circumstances. Overall, MMO games offer a powerful social science data generator that offers insights into real-world social problems (such as organised criminal networks) that are typically difficult to examine.
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Proceedings of the 11th ACM Conference on Web Science
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2037-12-31
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