期刊
JOURNAL OF CRIMINAL JUSTICE
卷 46, 期 -, 页码 52-63出版社
ELSEVIER
DOI: 10.1016/j.jcrimjus.2016.03.002
关键词
Ambient population; Crime pattern analysis; Clustering; Social media
资金
- Economic and Social Research Council (ESRC) [ES/L009900/1]
- ESRC [ES/L009900/1, ES/L011891/1] Funding Source: UKRI
- Economic and Social Research Council [ES/L009900/1, ES/L011891/1] Funding Source: researchfish
Purpose: Crime analysts need accurate population-at-risk measures to quantify crime rates. This research evaluates five measures to find the most suitable ambient population-at-risk estimate for 'theft from the person' crimes. Method: 1. Collect 'ambient' datasets: the 2011 Census, aggregate mobile telephone locations, and social media. 2. Correlate the population measures against crime volumes to identify the strongest predictor. 3. Use the G(i)* statistic to identify statistically significant clusters of crime under alternative denominators. 4. Explore the locations of clusters, comparing those that are significant under ambient and residential population estimates. Results and Discussion: The research identifies the Census workday population as the most appropriate population-at-risk measure. It also highlights areas that exhibit statistically significant rates using both the ambient and residential denominators. This hints at an environmental backcloth that is indicative of both crime generators and attractors - i.e. places that attract large numbers of people for non-crime purposes (generators) as well as places that are used specifically for criminal activity (attractors). Regions that are largely residential and yet only exhibit hotspots under the ambient population might be places with a higher proportion of crime attractors to stimulate crime, but fewer generators to attract volumes of people. (C) 2016 The Authors. Published by Elsevier Ltd.
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