Book chapter 695 views
A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison
Sara Correia-Hopkins 
The Crime Data Handbook
Swansea University Author:
Sara Correia-Hopkins
Abstract
The potential of administrative data to generate new insights and inform policy and practice is increasingly being explored by researchers and public authorities. The study of cybercrime is no exception, as for example, police recorded crime data can help better understand repeat victimisation trend...
| Published in: | The Crime Data Handbook |
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| Published: |
Bristol University Press
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa62010 |
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| Abstract: |
The potential of administrative data to generate new insights and inform policy and practice is increasingly being explored by researchers and public authorities. The study of cybercrime is no exception, as for example, police recorded crime data can help better understand repeat victimisation trends, as well as crime and victimisation trends within small geographies. These types of insight are key to determining what an adequate police response ‘on the ground’ should look like. However, the quality of these data has seldom been systematically analysed. Based on the author’s previous studies (Correia, 2022) and a review of recent literature, this chapter illustrates a framework for assessing the quality of police recorded cybercrime data, by comparing the data collected in the UK by Action Fraud (AF) and the USA by the Internet Crime Complaint Centre (IC3). The strengths and limitations of these data are grouped into four themes, closely aligned with the quality dimensions widely used by statistical authorities including 1) relevance, 2) accuracy and reliability, 3) coherence and comparability, and 4) accessibility and timeliness (Eurostat, 2019). This framework highlights the need for an intimate knowledge of the data collection mechanisms, to assess the quality of police recorded cybercrime data and make the most of its affordances. This chapter should therefore be useful to users of police recorded cybercrime data, beyond the AF/IC3 examples. Recommendations are made for data quality improvements, which will enable the production of better insights for crime prevention, investigation, and victim support. |
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| College: |
Faculty of Humanities and Social Sciences |
| Funders: |
This work was partly funded by the Economic and Social Research Council/UK Research & Innovation. In addition, the author gratefully acknowledges the support received from Swansea University’s Legal Innovation Lab Wales, part funded by the European Regional Development Fund through the Welsh Government. |