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A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison

Sara Correia-Hopkins Orcid Logo

The Crime Data Handbook

Swansea University Author: Sara Correia-Hopkins Orcid Logo

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...

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Published in: The Crime Data Handbook
Published: Bristol University Press
URI: https://cronfa.swan.ac.uk/Record/cronfa62010
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first_indexed 2022-11-23T10:02:44Z
last_indexed 2023-04-19T03:22:18Z
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spelling v2 62010 2022-11-23 A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison 2ba1ee45d427797148e7fa052da4de59 0000-0003-0261-6872 Sara Correia-Hopkins Sara Correia-Hopkins true false 2022-11-23 LAWD 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. Book chapter The Crime Data Handbook Bristol University Press 0 0 0 0001-01-01 COLLEGE NANME Law COLLEGE CODE LAWD Swansea University Not Required 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. 2023-07-28T18:13:44.7285710 2022-11-23T09:53:33.6553309 Faculty of Humanities and Social Sciences Hilary Rodham Clinton School of Law Sara Correia-Hopkins 0000-0003-0261-6872 1
title A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison
spellingShingle A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison
Sara Correia-Hopkins
title_short A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison
title_full A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison
title_fullStr A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison
title_full_unstemmed A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison
title_sort A framework for measuring the quality of police recorded cybercrime data, illustrated through a UK/USA comparison
author_id_str_mv 2ba1ee45d427797148e7fa052da4de59
author_id_fullname_str_mv 2ba1ee45d427797148e7fa052da4de59_***_Sara Correia-Hopkins
author Sara Correia-Hopkins
author2 Sara Correia-Hopkins
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hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str Hilary Rodham Clinton School of Law{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}Hilary Rodham Clinton School of Law
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description 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.
published_date 0001-01-01T18:13:39Z
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