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A framework for estimating crime location choice based on awareness space 基于感知空间的犯罪地点选择估计框架
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-11-04 DOI: 10.1186/s40163-020-00132-7
Sophie Curtis-Ham, W. Bernasco, O. Medvedev, D. Polaschek
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引用次数: 12
A machine learning analysis of serious misconduct among Australian police 对澳大利亚警方严重不当行为的机器学习分析
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-10-31 DOI: 10.1186/s40163-020-00133-6
Timothy I. C. Cubitt, K. Wooden, K. Roberts
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引用次数: 10
Unsupervised identification of crime problems from police free-text data 从警方自由文本数据中无监督识别犯罪问题
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-10-07 DOI: 10.1186/s40163-020-00127-4
Daniel Birks, Alex Coleman, David Jackson
We present a novel exploratory application of unsupervised machine-learning methods to identify clusters of specific crime problems from unstructured modus operandi free-text data within a single administrative crime classification. To illustrate our proposed approach, we analyse police recorded free-text narrative descriptions of residential burglaries occurring over a two-year period in a major metropolitan area of the UK. Results of our analyses demonstrate that topic modelling algorithms are capable of clustering substantively different burglary problems without prior knowledge of such groupings. Subsequently, we describe a prototype dashboard that allows replication of our analytical workflow and could be applied to support operational decision making in the identification of specific crime problems. This approach to grouping distinct types of offences within existing offence categories, we argue, has the potential to support crime analysts in proactively analysing large volumes of modus operandi free-text data—with the ultimate aims of developing a greater understanding of crime problems and supporting the design of tailored crime reduction interventions.
我们介绍了一种新颖的无监督机器学习方法的探索性应用，该方法可从单一行政犯罪分类中的非结构化作案手法自由文本数据中识别出特定犯罪问题群组。为了说明我们提出的方法，我们分析了警方记录的两年内发生在英国一个大都市地区的住宅盗窃案的自由文本叙述描述。我们的分析结果表明，主题建模算法能够在不事先了解此类分组的情况下对实质性不同的入室盗窃问题进行聚类。随后，我们介绍了一个仪表板原型，该仪表板可以复制我们的分析工作流程，并可用于支持识别特定犯罪问题的业务决策。我们认为，这种在现有犯罪类别中对不同类型的犯罪进行分组的方法有可能支持犯罪分析人员主动分析大量的作案手法自由文本数据，其最终目的是加深对犯罪问题的了解，并支持设计有针对性的减少犯罪干预措施。
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引用次数: 0
Unsupervised identification of crime problems from police free-text data 警方自由文本数据中犯罪问题的无监督识别
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-08-19 DOI: 10.31235/osf.io/8w73n
Daniel Birks, A. Coleman, Donald A. Jackson
We present a novel exploratory application of unsupervised machine-learning methods to identify clusters of specific crime problems from unstructured modus operandi free-text data within a single administrative crime classification. To illustrate our proposed approach, we analyse police recorded free-text narrative descriptions of residential burglaries occurring over a two-year period in a major metropolitan area of the UK. Results of our analyses demonstrate that topic modelling algorithms are capable of clustering substantively different burglary problems without prior knowledge of such groupings. Subsequently, we describe a prototype dashboard that allows replication of our analytical workflow and could be applied to support operational decision making in the identification of specific crime problems. This approach to grouping distinct types of offences within existing offence categories, we argue, has the potential to support crime analysts in proactively analysing large volumes of modus operandi free-text data—with the ultimate aims of developing a greater understanding of crime problems and supporting the design of tailored crime reduction interventions.
我们提出了一种新的探索性应用无监督机器学习方法，从单一行政犯罪分类中的非结构化无作案手法文本数据中识别特定犯罪问题集群。为了说明我们提出的方法，我们分析了警方记录的英国一个大城市地区两年内发生的住宅盗窃案的自由文本叙述描述。我们的分析结果表明，主题建模算法能够在事先不知道这些分组的情况下，对实质上不同的入室盗窃问题进行聚类。随后，我们描述了一个原型仪表板，该仪表板允许复制我们的分析工作流程，并可用于支持识别特定犯罪问题的操作决策。我们认为，这种在现有犯罪类别中对不同类型的犯罪进行分组的方法有可能支持犯罪分析师主动分析大量的无作案手法文本数据，最终目的是加深对犯罪问题的理解，并支持设计有针对性的减少犯罪干预措施。
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引用次数: 6
Too far for comfort? Situational access to emergency medical care and violent assault lethality 太远而不舒适？紧急情况下获得紧急医疗救助与暴力袭击的致命性
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-08-17 DOI: 10.1186/s40163-020-00124-7
Lucia Summers, Tiffany Gentry Rogers
This research demonstrates the relationship between situational access to emergency medical care and assault lethality, by comparing attempted and completed murders in Greater London, England, over a five-year period (N = 1512 victims). Access to emergency care was operationalised using the time taken to contact emergency services, the distance from the nearest ambulance station, and the distance to the nearest emergency department. Notification lags in excess of 1 h were associated with significantly higher lethality, after controlling for offence and victim characteristics. The distance predictors were non-significant, which could be due to observed distances in our urban setting being overwhelmingly short (< 5 miles) and homogeneous.
本研究通过比较英国大伦敦地区五年内未遂和已遂谋杀案（N = 1512 名受害者）的情况，展示了获得紧急医疗护理的情况与袭击致死率之间的关系。获得紧急医疗服务的可操作性包括联系急救服务所需的时间、距离最近的救护站的距离以及距离最近的急诊室的距离。在控制了犯罪和受害者特征之后，通知滞后超过1小时与更高的致死率明显相关。距离预测因子不显著，这可能是由于在我们的城市环境中观察到的距离绝大多数都很短（< 5 英里），而且很均匀。
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引用次数: 0
AI-enabled future crime 人工智能驱动的未来犯罪
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-08-05 DOI: 10.1186/s40163-020-00123-8
M. Caldwell, J. T. A. Andrews, T. Tanay, L. D. Griffin
A review was conducted to identify possible applications of artificial intelligence and related technologies in the perpetration of crime. The collected examples were used to devise an approximate taxonomy of criminal applications for the purpose of assessing their relative threat levels. The exercise culminated in a 2-day workshop on ‘AI & Future Crime’ with representatives from academia, police, defence, government and the private sector. The workshop remit was (i) to catalogue potential criminal and terror threats arising from increasing adoption and power of artificial intelligence, and (ii) to rank these threats in terms of expected victim harm, criminal profit, criminal achievability and difficulty of defeat. Eighteen categories of threat were identified and rated. Five of the six highest-rated had a broad societal impact, such as those involving AI-generated fake content, or could operate at scale through use of AI automation; the sixth was abuse of driverless vehicle technology for terrorist attack.
为确定人工智能和相关技术在犯罪中的可能应用，进行了一次审查。收集到的实例被用于设计犯罪应用的近似分类法，以评估其相对威胁程度。这项工作的高潮是举办了为期两天的 "人工智能与未来犯罪 "讲习班，来自学术界、警方、国防、政府和私营部门的代表参加了讲习班。研讨会的任务是：(i) 对人工智能的日益普及和强大所带来的潜在犯罪和恐怖威胁进行分类；(ii) 根据对受害者的预期伤害、犯罪收益、犯罪可实现性和挫败难度对这些威胁进行排序。确定并评定了 18 类威胁。评级最高的六类威胁中，有五类具有广泛的社会影响，如涉及人工智能生成的虚假内容，或可通过使用人工智能自动化进行大规模运作；第六类是滥用无人驾驶汽车技术进行恐怖袭击。
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引用次数: 0
Fraud against businesses both online and offline: crime scripts, business characteristics, efforts, and benefits 针对企业的在线和离线欺诈：犯罪脚本、企业特点、努力和收益
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-07-09 DOI: 10.1186/s40163-020-00119-4
Marianne Junger, Victoria Wang, Marleen Schlömer

This study analyses 300 cases of fraudulent activities against Dutch businesses, 100 from each of the following three categories: CEO-fraud, fraudulent contract, and ghost invoice. We examine crime scripts, key characteristics of targeted businesses, and the relationship between input criminal effort and output financial benefit. Results indicate that whilst all CEO-frauds are conducted online, most of the fraudulent contracts and ghost invoices are undertaken via offline means. Both Routine Activity Theory and Rational Choice Model are evidenced-fraudsters clearly take the business size and seasonality into account, and the input criminal effort and output criminal benefit are positively correlated. Having vigilant employees is evidenced as the most effective way of fraud prevention, both online and offline.

本研究分析了 300 起针对荷兰企业的欺诈活动案件，以下三类案件各占 100 起：CEO 欺诈案、欺诈合同案和幽灵发票案。我们研究了犯罪脚本、目标企业的主要特征以及投入的犯罪努力与产出的经济利益之间的关系。结果表明，虽然所有的首席执行官欺诈都是在网上进行的，但大多数欺诈合同和虚假发票都是通过离线方式进行的。例行活动理论和理性选择模型都证明了这一点--欺诈者显然考虑到了企业规模和季节性，而且投入的犯罪努力和产出的犯罪收益呈正相关。无论在线还是离线，提高员工的警惕性都被证明是最有效的防欺诈方法。
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引用次数: 0
Built environment attributes and crime: an automated machine learning approach 建筑环境属性与犯罪:一种自动化机器学习方法
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-07-08 DOI: 10.1186/s40163-020-00122-9
Kyle Dakin, Weizhi Xie, S. Parkinson, Saad Khan, Leanne Monchuk, Ken Pease
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引用次数: 8
RETRACTED ARTICLE: Do offenders avoid offending near home? A systematic review of the buffer zone hypothesis 文章撤回:违法者会避免在家附近犯案吗?对缓冲地带假说的系统回顾
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-05-27 DOI: 10.1186/s40163-020-00118-5
W. Bernasco, Remco van Dijke
{"title":"RETRACTED ARTICLE: Do offenders avoid offending near home? A systematic review of the buffer zone hypothesis","authors":"W. Bernasco, Remco van Dijke","doi":"10.1186/s40163-020-00118-5","DOIUrl":"https://doi.org/10.1186/s40163-020-00118-5","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00118-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65836055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Near-repeat victimization of sex crimes and threat incidents against women and girls in Tokyo, Japan 在日本东京，针对妇女和女孩的性犯罪和威胁事件几乎重复发生
IF 6.1 Q1 Social Sciences
Crime Science
Pub Date : 2020-05-13 DOI: 10.1186/s40163-020-00114-9
Mamoru Amemiya, T. Nakaya, T. Shimada
{"title":"Near-repeat victimization of sex crimes and threat incidents against women and girls in Tokyo, Japan","authors":"Mamoru Amemiya, T. Nakaya, T. Shimada","doi":"10.1186/s40163-020-00114-9","DOIUrl":"https://doi.org/10.1186/s40163-020-00114-9","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00114-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65835998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
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