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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
Crime Science Pub Date : 2020-11-04 DOI: 10.1186/s40163-020-00132-7
Sophie Curtis-Ham, W. Bernasco, O. Medvedev, D. Polaschek
{"title":"A framework for estimating crime location choice based on awareness space","authors":"Sophie Curtis-Ham, W. Bernasco, O. Medvedev, D. Polaschek","doi":"10.1186/s40163-020-00132-7","DOIUrl":"https://doi.org/10.1186/s40163-020-00132-7","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00132-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43361221","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: 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
Crime Science Pub Date : 2020-10-31 DOI: 10.1186/s40163-020-00133-6
Timothy I. C. Cubitt, K. Wooden, K. Roberts
{"title":"A machine learning analysis of serious misconduct among Australian police","authors":"Timothy I. C. Cubitt, K. Wooden, K. Roberts","doi":"10.1186/s40163-020-00133-6","DOIUrl":"https://doi.org/10.1186/s40163-020-00133-6","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00133-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65836688","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: 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
Crime Science Pub Date : 2020-10-07 DOI: 10.1186/s40163-020-00127-4
Daniel Birks, Alex Coleman, David Jackson
{"title":"Unsupervised identification of crime problems from police free-text data","authors":"Daniel Birks, Alex Coleman, David Jackson","doi":"10.1186/s40163-020-00127-4","DOIUrl":"https://doi.org/10.1186/s40163-020-00127-4","url":null,"abstract":"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.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882402","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: 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
Crime Science Pub Date : 2020-08-19 DOI: 10.31235/osf.io/8w73n
Daniel Birks, A. Coleman, Donald A. Jackson
{"title":"Unsupervised identification of crime problems from police free-text data","authors":"Daniel Birks, A. Coleman, Donald A. Jackson","doi":"10.31235/osf.io/8w73n","DOIUrl":"https://doi.org/10.31235/osf.io/8w73n","url":null,"abstract":"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.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43791855","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: 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
Crime Science Pub Date : 2020-08-17 DOI: 10.1186/s40163-020-00124-7
Lucia Summers, Tiffany Gentry Rogers
{"title":"Too far for comfort? Situational access to emergency medical care and violent assault lethality","authors":"Lucia Summers, Tiffany Gentry Rogers","doi":"10.1186/s40163-020-00124-7","DOIUrl":"https://doi.org/10.1186/s40163-020-00124-7","url":null,"abstract":"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.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882543","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: 0
AI-enabled future crime 人工智能驱动的未来犯罪
IF 6.1
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
{"title":"AI-enabled future crime","authors":"M. Caldwell, J. T. A. Andrews, T. Tanay, L. D. Griffin","doi":"10.1186/s40163-020-00123-8","DOIUrl":"https://doi.org/10.1186/s40163-020-00123-8","url":null,"abstract":"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.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882462","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: 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
Crime Science Pub Date : 2020-07-09 DOI: 10.1186/s40163-020-00119-4
Marianne Junger, Victoria Wang, Marleen Schlömer
{"title":"Fraud against businesses both online and offline: crime scripts, business characteristics, efforts, and benefits","authors":"Marianne Junger, Victoria Wang, Marleen Schlömer","doi":"10.1186/s40163-020-00119-4","DOIUrl":"https://doi.org/10.1186/s40163-020-00119-4","url":null,"abstract":"<p>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.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882464","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: 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
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
{"title":"Built environment attributes and crime: an automated machine learning approach","authors":"Kyle Dakin, Weizhi Xie, S. Parkinson, Saad Khan, Leanne Monchuk, Ken Pease","doi":"10.1186/s40163-020-00122-9","DOIUrl":"https://doi.org/10.1186/s40163-020-00122-9","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00122-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65836104","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: 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
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
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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