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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 realworld 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.

Policing agencies are adopting or trialling facial recognition technology (FRT). While the public tend to be sceptical of any new technology, public support is needed for both legitimacy and strong police–citizen relationships. The media can greatly influence not only the public agenda, but also the attitudes and sentiments towards the topic. This study takes an agenda-setting perspective to explore social media’s portrayal of police use of FRT. To do this, a sentiment analysis was conducted of 203 YouTube videos. Overall, the discourse was mostly positive for the use of FRT by police. An examination of the emotional language found high levels of surprise and anticipation along with sadness and fear. Notably, trust was expressed only in low levels. These findings inform the development of police practices and policies when adopting new technologies and the communication strategies of such policies and practices.