Police crime information systems contain modus operandi (MO) fields which provide brief text descriptions of the circumstances surrounding crime events and the actions taken by offenders to commit them. This Thesis aims to assess the feasibility of undertaking systematic analysis of these descriptions for high volume crimes. In particular, it seeks to ask the following three questions: 1) Are police recorded MO data a potential source of actionable intelligence to inform crime prevention? 2) Can techniques drawn from computer-aided text analysis be used to identify meaningful patterns in MO data for high volume crimes? 3) Do conceptual frameworks add value to the analysis and interpretation of patterns in MOs? The study focuses on a sample of theft from the person and robbery of personal property offences (n~30,000). Although existing studies have utilised similar data, they have tended to focus on crime detection and have been beset with problems of data quality. To explore these aims, it was first necessary to conduct a thorough review of MO fields to identify the challenges they present for analysis. Problems identified include various types of error but a more prominent challenge is the inherent flexibility found within natural language, i.e. human language as opposed to languages that are artificially constructed. Based on the data review, it was possible to select, and develop, appropriate techniques of computer-aided content analysis to process the data ready for further statistical investigation. In particular, a cluster analysis successfully identified and classified groups of offences based on similarities in their MO fields. The findings from the analysis were interpreted using two conceptual frameworks, the conjunction of criminal opportunity and crime scripts, both of which are informed by situational crime theories. The thesis identified that the benefits of these frameworks were twofold. As methods of analysis the frameworks ensure that the interpretation of results is systematic. As theoretical frameworks they provide an explicit link between patterns in the data, findings from previous literature, theories of crime causation and methods of prevention. Importantly, using the two frameworks together helps to build an improved understanding of offender's ability both to cope with and to exploit crime situations. The thesis successfully demonstrates that MO fields contain a potential source of intelligence relevant to both practical crime prevention and research, and that it is possible to extract this information using innovative computer-aided textual analysis techniques. The research undertaken served as a pathfinding exercise developing what amounts to a replicable technique applicable to datasets from other localities and other crime types. However, the analysis process is neither fully objective nor automated. The thesis concluded that criminological frameworks are a pre-requisite to the interpretation of this intelligence although the research questioned the strict categories and hierarchies imposed by the frameworks which do not entirely reflect the flexibilities of real-life crime commission.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:688339 |
Date | January 2016 |
Creators | Rogerson, Michelle |
Contributors | Hirschfield, Alex |
Publisher | University of Huddersfield |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://eprints.hud.ac.uk/id/eprint/28709/ |
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