This talk was recorded at Europe’s first Computational Social Science conference at the University of Warwick in June 2014, hosted by the Data Science Lab at Warwick Business School.

ABSTRACT | The spatio-temporal distribution of crime in urban areas has been the subject of a large volume of empirical research, and is a topic with immediate relevance to policy. In recent years, a number of models have been proposed which seek to describe the occurrence of crime by encoding criminological theories of offender behaviour, and which may ultimately be used predictively. While these show promise in terms of their ability to generate characteristic patterns (such as hotspots), however, few such models take into account the influence of urban form; in particular, the effect of the street network. Using data from London and Birmingham, I will demonstrate that significant relationships exist at the street segment level between crime risk and a number of network metrics, including those intended to predict levels of use and awareness. I will discuss the implications of this for crime modelling, before introducing a model which is situated on a network and allows a number of these considerations to be accounted for. I will then show how the model can be used to explore a number of policy issues, related to policing and urban design, using both simulated and analytic results.

BIOGRAPHY | Toby Davies is a research associate in the Department of Civil, Environmental and Geomatic Engineering at University College London. After completing an MMath in Mathematics at the University of Oxford, he joined the SECReT PhD program at UCL, where he was co-supervised between the departments of Mathematics and Security Science. His research interests concern the use of approaches from complexity science in the context of crime; in particular, the measurement of space-time clustering, the influence of street networks on crime, and the evolution of large-scale riots. He now works on the Crime, Policing and Citizenship project at UCL, studying the interaction between crime occurrence, policing activity and public perception.

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