Crime Science最新文献

{"title":"\"Show this thread\": policing, disruption and mobilisation through Twitter. An analysis of UK law enforcement tweeting practices during the Covid-19 pandemic.","authors":"Manja Nikolovska, Shane D Johnson, Paul Ekblom","doi":"10.1186/s40163-020-00129-2","DOIUrl":"10.1186/s40163-020-00129-2","url":null,"abstract":"<p><p>Crisis and disruption are often unpredictable and can create opportunities for crime. During such times, policing may also need to meet additional challenges to handle the disruption. The use of social media by officials can be essential for crisis mitigation and crime reduction. In this paper, we study the use of Twitter for crime mitigation and reduction by UK police (and associated) agencies in the early stages of the Covid-19 pandemic. Our findings suggest that whilst most of the tweets from our sample concerned issues that were not specifically about crime, especially during the first stages of the pandemic, there was a significant increase in tweets about fraud, cybercrime and domestic abuse. There was also an increase in retweeting activity as opposed to the creation of original messages. Moreover, in terms of the impact of tweets, as measured by the rate at which they are retweeted, followers were more likely to 'spread the word' when the tweet was content-rich (discussed a crime specific matter and contained media), and account holders were themselves more active on Twitter. Considering the changing world we live in, criminal opportunity is likely to evolve. To help mitigate this, policy makers and researchers should consider more systematic approaches to developing social media communication strategies for the purpose of crime mitigation and reduction during disruption and change more generally. We suggest a framework for so doing.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":"20"},"PeriodicalIF":3.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38531950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Initial evidence on the relationship between the coronavirus pandemic and crime in the United States.","authors":"Matthew P J Ashby","doi":"10.1186/s40163-020-00117-6","DOIUrl":"https://doi.org/10.1186/s40163-020-00117-6","url":null,"abstract":"<p><p>The COVID-19 pandemic led to substantial changes in the daily activities of millions of Americans, with many businesses and schools closed, public events cancelled and states introducing stay-at-home orders. This article used police-recorded open crime data to understand how the frequency of common types of crime changed in 16 large cities across the United States in the early months of 2020. Seasonal auto-regressive integrated moving average (SARIMA) models of crime in previous years were used to forecast the expected frequency of crime in 2020 in the absence of the pandemic. The forecasts from these models were then compared to the actual frequency of crime during the early months of the pandemic. There were no significant changes in the frequency of serious assaults in public or (contrary to the concerns of policy makers) any change to the frequency of serious assaults in residences. In some cities, there were reductions in residential burglary but little change in non-residential burglary. Thefts of motor vehicles decreased in some cities while there were diverging patterns of thefts from motor vehicles. These results are used to make suggestions for future research into the relationships between the coronavirus pandemic and different crimes.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":"6"},"PeriodicalIF":6.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00117-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37978110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Routine activity effects of the Covid-19 pandemic on burglary in Detroit, March, 2020.","authors":"Marcus Felson, Shanhe Jiang, Yanqing Xu","doi":"10.1186/s40163-020-00120-x","DOIUrl":"10.1186/s40163-020-00120-x","url":null,"abstract":"<p><p>The spread of the coronavirus has led to containment policies in many places, with concomitant shifts in routine activities. Major declines in crime have been reported as a result. However, those declines depend on crime type and may differ by parts of a city and land uses. This paper examines burglary in Detroit, Michigan during the month of March, 2020, a period of considerable change in routine activities. We examine 879 block groups, separating those dominated by residential land use from those with more mixed land use. We divide the month into three periods: pre-containment, transition period, and post-containment. Burglaries increase in block groups with mixed land use, but not blocks dominated by residential land use. The impact of containment policies on burglary clarifies after taking land use into account.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":"10"},"PeriodicalIF":6.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309695/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38297535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review on spatial crime forecasting.","authors":"Ourania Kounadi, Alina Ristea, Adelson Araujo, Michael Leitner","doi":"10.1186/s40163-020-00116-7","DOIUrl":"10.1186/s40163-020-00116-7","url":null,"abstract":"<p><strong>Background: </strong>Predictive policing and crime analytics with a spatiotemporal focus get increasing attention among a variety of scientific communities and are already being implemented as effective policing tools. The goal of this paper is to provide an overview and evaluation of the state of the art in spatial crime forecasting focusing on study design and technical aspects.</p><p><strong>Methods: </strong>We follow the PRISMA guidelines for reporting this systematic literature review and we analyse 32 papers from 2000 to 2018 that were selected from 786 papers that entered the screening phase and a total of 193 papers that went through the eligibility phase. The eligibility phase included several criteria that were grouped into: (a) the publication type, (b) relevance to research scope, and (c) study characteristics.</p><p><strong>Results: </strong>The most predominant type of forecasting inference is the hotspots (i.e. binary classification) method. Traditional machine learning methods were mostly used, but also kernel density estimation based approaches, and less frequently point process and deep learning approaches. The top measures of evaluation performance are the Prediction Accuracy, followed by the Prediction Accuracy Index, and the F1-Score. Finally, the most common validation approach was the train-test split while other approaches include the cross-validation, the leave one out, and the rolling horizon.</p><p><strong>Limitations: </strong>Current studies often lack a clear reporting of study experiments, feature engineering procedures, and are using inconsistent terminology to address similar problems.</p><p><strong>Conclusions: </strong>There is a remarkable growth in spatial crime forecasting studies as a result of interdisciplinary technical work done by scholars of various backgrounds. These studies address the societal need to understand and combat crime as well as the law enforcement interest in almost real-time prediction.</p><p><strong>Implications: </strong>Although we identified several opportunities and strengths there are also some weaknesses and threats for which we provide suggestions. Future studies should not neglect the juxtaposition of (existing) algorithms, of which the number is constantly increasing (we enlisted 66). To allow comparison and reproducibility of studies we outline the need for a protocol or standardization of spatial forecasting approaches and suggest the reporting of a study's key data items.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":"7"},"PeriodicalIF":6.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319308/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38126484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Age-period-cohort effects in half a century of motor vehicle theft in the United States.","authors":"Anthony Dixon,&nbsp;Graham Farrell","doi":"10.1186/s40163-020-00126-5","DOIUrl":"https://doi.org/10.1186/s40163-020-00126-5","url":null,"abstract":"<p><p>Adopting and refining O'Brien's S-constraint approach, we estimate age-period-cohort effects for motor vehicle theft offences in the United States for over half a century from 1960. Taking the well-established late-teen peak offending age as given, we find period effects reducing theft in the 1970 s, and period, but particularly cohort effects, reducing crime from the 1990s onwards. We interpret these effects as consistent with variation in the prevailing level of crime opportunities, particularly the ease with which vehicles could be stolen. We interpret the post-1990s cohort effect as triggered by a period effect that operated differentially by age: improved vehicle security reduced juvenile offending dramatically, to the extent that cohorts experienced reduced offending across the life-course. This suggests the prevailing level of crime opportunities in juvenile years is an important determinant of rates of onset and continuance in offending in birth cohorts. We outline additional implications for research and practice.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":"17"},"PeriodicalIF":6.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00126-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38462314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Minor covid-19 association with crime in Sweden.","authors":"Manne Gerell,&nbsp;Johan Kardell,&nbsp;Johanna Kindgren","doi":"10.1186/s40163-020-00128-3","DOIUrl":"https://doi.org/10.1186/s40163-020-00128-3","url":null,"abstract":"<p><p>The covid-19 disease has a large impact on life across the globe, and this could potentially include impacts on crime. The present study describes how crime has changed in Sweden during ten weeks after the government started to implement interventions to reduce spread of the disease. Sweden has undertaken smaller interventions than many other countries and is therefore a particularly interesting case to study. The first major interventions in Sweden were implemented in the end of week 11 (March 12th) in the year 2020, and we analyze police reported crimes through week 21 (ending May 24th). Descriptive statistics are provided relative to expected levels with 95% confidence intervals for eight crime types. We find that total crime, assaults, pickpocketing and burglary have decreased significantly, personal robberies and narcotics crime are unchanged. Vandalism possibly increased somewhat but is hard to draw any firm conclusions on. The reductions are fairly small for most crime types, in the 5-20% range, with pickpocketing being the biggest exception noting a 59% drop relative to expected levels.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":"19"},"PeriodicalIF":6.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00128-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38598241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of subgroups of terror attacks with shared characteristics for the purpose of preventing mass-casualty attacks: a data-mining approach","authors":"Gonen Singer, Maya Golan","doi":"10.1186/s40163-019-0109-9","DOIUrl":"https://doi.org/10.1186/s40163-019-0109-9","url":null,"abstract":"Security and intelligence agencies around the world invest considerable resources in preventing terrorist attacks, as these may cause strategic damage, national demoralization, infringement of sovereignty, and government instability. Recently, data-mining techniques have evolved to allow identification of patterns and associations in criminal data that were not apparent using traditional analysis. The aim of this paper is to illustrate how to use interpretable classification algorithms to identify subgroups (“patterns”) of terrorist incidents that share common characteristics and that result in mass fatalities. This approach can produce insights far beyond those of conventional macro-level studies that use hypothesis-testing and regression models. In addition to this methodological contribution, from a practical perspective, exploring the characteristics identified in the “patterns” can lead to prevention strategies, such as alteration of the physical or systemic environment. This is in line with situational crime prevention (SCP) theory. We apply our methodology to the Global Terrorism Database (GTD). We present three examples in which terror attacks that are described by a particular pattern (set of characteristics) resulted in a high probability of mass casualties, while attacks that differ in just one of these characteristics (i.e., month of attack, geographical area targeted, or type of attack) resulted in far fewer casualties. We propose exploration of the differentiating characteristic as a means of reducing the probability of mass-fatality terrorist incidents.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"24 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882405","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}

{"title":"Beyond crime rates and community surveys: a new approach to police accountability and performance measurement","authors":"Tarah Hodgkinson, T. Caputo, M. L. McIntyre","doi":"10.1186/s40163-019-0108-x","DOIUrl":"https://doi.org/10.1186/s40163-019-0108-x","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"8 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-019-0108-x","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65835932","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}

{"title":"What about cyberspace (and cybercrime alongside it)? A reply to Farrell and Birks “Did cybercrime cause the crime drop?”","authors":"Fernando Miró-Llinares, Asier Moneva","doi":"10.1186/s40163-019-0107-y","DOIUrl":"https://doi.org/10.1186/s40163-019-0107-y","url":null,"abstract":"In this paper we question Farrell and Birks’ assertion of the emergence of cybercrime as an invalid explanation for the crime drop. Alternatively to the “cybercrime hypothesis”, we propose two non-exclusive hypotheses that highlight the essential role of cyberspace as an environment that has shifted criminal opportunities from physical to virtual space, which reflects on crime trends. The first hypothesis posits that the more time spent at home by many young people due to video games and online leisure activities, among other factors, could have had an impact on the juvenile crime drop. The second hypothesis states that the appearance of cyberspace has led to a shift in opportunities from physical space to cyberspace. This could have led to an increase in property-related criminal activity connected to the Internet to the detriment of physical crime which would not be reflected in the statistics. Both premises are supported by empirical evidence.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"58 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2019-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882401","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}

{"title":"Toward a test of the “Law of Crime Concentration” in Japanese cities: a geographical crime analysis in Tokyo and Osaka","authors":"Mamoru Amemiya, Tomoya Ohyama","doi":"10.1186/s40163-019-0106-z","DOIUrl":"https://doi.org/10.1186/s40163-019-0106-z","url":null,"abstract":"This brief report aims to reveal crime concentration at the district level in Tokyo and Osaka, Japan, two cities characterized by low crime rates. Eight types of property crimes that occurred between 2008 and 2017 in Tokyo and Osaka and had been aggregated by the census enumeration district were analyzed using the Gini coefficient based on the Poisson-Gamma method. The results indicated three patterns. First, crime concentration was identified. Second, the degree of concentration depended upon crime type. Commercial burglary was the most concentrated crime type, and theft from vehicle and theft from vending machine were the most dispersed. Third, crime concentration patterns either remained stable or became more concentrated over time. Additionally, while theft of bicycle was found to display stable concentration levels over time, the concentration level of purse snatching was fluid. On the basis of the results, this report discusses the possibility of establishing the “Law of Crime Concentration” (LCC) in two Japanese cities.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"110 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2019-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882466","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}