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每周犯罪集中情况。

Weekly Crime Concentration.

作者信息

Prieto Curiel Rafael

机构信息

Centre for Advanced Spatial Analysis, University College London, London, UK.

出版信息

J Quant Criminol. 2023;39(1):97-124. doi: 10.1007/s10940-021-09533-6. Epub 2021 Sep 1.

DOI:10.1007/s10940-021-09533-6
PMID:34483469
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8408821/
Abstract

OBJECTIVES

Examine and visualise the temporal concentration of different crime types and detect if their intensity varies through distinct moments of the week.

METHODS

The "heartbeat of the crime signal" is constructed by overlapping the weekly time they were suffered. This study is based on more than 220,000 crimes reported to the Mexico City Police Department between January 2016 and March 2020 to capture the day and time of crimes and detect moments of the week in which the intensity exceeds the average frequency. A new metric for the temporal concentration of crime is constructed for different types of crime and regions of the city based on the corresponding heartbeats.

RESULTS

The temporal concentration of crime is a stable signature of different types of crime. The intensity of robberies and theft is more homogeneous from Monday to Sunday, but robberies of a bank user are highly concentrated in a week, meaning that few hours of the week capture most of the burning moments. The concentration is not homogeneously distributed in the city, with some regions experiencing a much higher temporal concentration of crime.

CONCLUSIONS

Crime is highly concentrated when observed in its weekly patterns, but different types of crime and regions exhibit substantially distinct concentration levels. The temporal trace indicates specific moments for the burning times of different types of crime, which is a critical element of a policing strategy.

摘要

目的

研究并可视化不同犯罪类型的时间集中度，检测其强度在一周的不同时段是否有所变化。

方法

通过重叠犯罪发生的每周时间来构建“犯罪信号的心跳”。本研究基于2016年1月至2020年3月期间向墨西哥城警察局报告的22万多起犯罪案件，以获取犯罪的日期和时间，并检测一周中强度超过平均频率的时段。基于相应的“心跳”，为不同类型的犯罪和城市区域构建了一种新的犯罪时间集中度指标。

结果

犯罪的时间集中度是不同类型犯罪的一个稳定特征。抢劫和盗窃的强度从周一到周日更为均匀，但针对银行用户的抢劫在一周内高度集中，这意味着一周中的少数几个小时涵盖了大部分高发时刻。这种集中度在城市中分布不均，一些区域的犯罪时间集中度要高得多。

结论

从每周模式来看，犯罪高度集中，但不同类型的犯罪和区域呈现出截然不同的集中程度。时间轨迹表明了不同类型犯罪高发时间的特定时刻，这是警务策略的一个关键要素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/09cfd4e92efc/10940_2021_9533_Fig13_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/f8b8060d2cac/10940_2021_9533_Fig10_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/7f4c10a9ddbf/10940_2021_9533_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/09cfd4e92efc/10940_2021_9533_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/9aca6c5ec97a/10940_2021_9533_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/02c615457323/10940_2021_9533_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/70a62cc40330/10940_2021_9533_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/c8c94f5da6e4/10940_2021_9533_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/2fb5b54cdcb2/10940_2021_9533_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/5c1c5d3e31ee/10940_2021_9533_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/d1c2b889cfbd/10940_2021_9533_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/759461f7a155/10940_2021_9533_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/56dc11c7b619/10940_2021_9533_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/f8b8060d2cac/10940_2021_9533_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/4aceff209168/10940_2021_9533_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/7f4c10a9ddbf/10940_2021_9533_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8527/8408821/09cfd4e92efc/10940_2021_9533_Fig13_HTML.jpg

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Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.犯罪的时空变化：常规活动理论视角
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