Crime, Policing and Citizenship (CPC) – Space-Time Interactions of Dynamic Networks has been a major UK EPSRC-funded research project. It has been a multidisciplinary collaboration of geoinfor-matics, crime science, computer science and geog-raphy within University College London (UCL), in partnership with the Metropolitan Police Service (MPS). The aim of the project has been to develop new methods and applications in space-time analyt-ics and emergent network complexity, in order to uncover patterning and interactions in crime, polic-ing and citizen perceptions. The work carried out throughout the project will help inform policing at a range of scales, from the local to the city-wide, with the goal of reducing both crime and the fear of crime. The CPC project is timely given the tremendous challenges facing policing in big cities nationally and globally, as consequences of changes in society, population structure and economic well-being. It addresses these issues through an intelligent ap-proach to data-driven policing, using daily reported crime statistics, GPS traces of foot and vehicular patrols, surveys of public attitudes and geo-tem-poral demographic data of changing community structure. The analytic focus takes a spatio-temporal perspective, reflecting the strong spatial and tem-poral integration of criminal, policing and citizen activities. Street networks are used throughout as a basis for analysis, reflecting their role as a key determinant of urban structure and the substrate on which crime and policing take place. The project has presented a manifesto for ‘in-telligent policing’ which embodies the key issues arising in the transition from Big Data into action-able insights. Police intelligence should go beyond current practice, incorporating not only the predic-tion of events, but also how to respond to them, and how to evaluate the actions taken. Cutting-edge network-based crime prediction methods have been developed to accurately predict crime risks at the street segment level, helping police forces to focus resources in the right places at the right times. Methods and tools have been implemented to support senior offices in strategic planning, and to provide guidance to frontline of-ficers in daily patrolling. To evaluate police perfor-mance, models and tools have been developed to aid identification of areas requiring greater attention, and to analyse the patrolling behaviours of officers. Methods to understand and model confidence in po-licing have also been explored, suggesting strategies by which confidence in the police can be improved in different population segments and neighbour-hood areas. A number of tools have been developed dur-ing the course of the project including data-driven methods for crime prediction and for performance evaluation. We anticipate that these will ultimately be adopted in daily policing practice and will play an important role in the modernisation of policing. Furthermore, we believe that the approaches to the building of public trust and confidence that we suggest will contribute to the transformation and improvement of the relationship between the public and police.EXECUTIVE SUMMARY
CPC: Crime, Policing and Citizenship – Intelligent policing and big data.. Available from: https://www.researchgate.net/publication/303539780_CPC_Crime_Policing_and_Citizenship_-_Intelligent_policing_and_big_data [accessed Oct 23, 2016].
Policing: An International Journal of Police Strategies & Management, (25)3, 530–542.
Complex issues, Complex networks, and Complex Systems