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Further rejection of the cybercrime hypothesis 进一步否定网络犯罪假说
IF 6.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-05-12 DOI: 10.1186/s40163-020-00113-w
Graham Farrell, Daniel Birks
We recently rejected the hypothesis that increases in cybercrime may have caused the international crime drop. Critics subsequently argued that offenders switched from physical crime to cybercrime in recent years, and that lifestyle changes due to ‘leisure IT’ may have caused the international crime drop. Here we explain how the critics misrepresented our argument and do not appear to introduce anything new.
我们最近否定了网络犯罪增加可能导致国际犯罪率下降的假设。批评者随后认为,近年来犯罪分子从人身犯罪转向网络犯罪,"休闲信息技术 "导致的生活方式改变可能是国际犯罪率下降的原因。在此,我们解释了批评者是如何歪曲我们的论点的,而且似乎并没有提出任何新的观点。
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引用次数: 0
Initial evidence on the relationship between the coronavirus pandemic and crime in the United States 关于冠状病毒大流行与美国犯罪之间关系的初步证据
IF 6.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-04-27 DOI: 10.31235/osf.io/ep87s
M. Ashby
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.
2019冠状病毒病大流行导致数百万美国人的日常活动发生重大变化,许多企业和学校关闭,公共活动取消,各州实施居家令。本文使用警方记录的公开犯罪数据来了解2020年前几个月美国16个大城市常见类型犯罪的频率变化情况。使用往年的季节性自回归综合移动平均(SARIMA)犯罪模型来预测2020年在没有大流行的情况下的预期犯罪频率。然后将这些模型的预测结果与大流行最初几个月的实际犯罪频率进行比较。在公共场所发生严重袭击的频率没有显著变化,或者(与政策制定者的担忧相反)在住宅发生严重袭击的频率没有任何变化。在一些城市,住宅盗窃案有所减少,但非住宅盗窃案变化不大。部分城市机动车盗窃案有所减少,但机动车盗窃案的模式存在差异。这些结果用于为未来研究冠状病毒大流行与不同犯罪之间的关系提出建议。
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引用次数: 169
Learning to rank spatio-temporal event hotspots 学习对时空事件热点进行排序
IF 6.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-03-20 DOI: 10.1186/s40163-020-00112-x
George Mohler, Michael Porter, Jeremy Carter, Gary LaFree
Background Crime, traffic accidents, terrorist attacks, and other space-time random events are unevenly distributed in space and time. In the case of crime, hotspot and other proactive policing programs aim to focus limited resources at the highest risk crime and social harm hotspots in a city. A crucial step in the implementation of these strategies is the construction of scoring models used to rank spatial hotspots. While these methods are evaluated by area normalized Recall@k (called the predictive accuracy index), models are typically trained via maximum likelihood or rules of thumb that may not prioritize model accuracy in the top k hotspots. Furthermore, current algorithms are defined on fixed grids that fail to capture risk patterns occurring in neighborhoods and on road networks with complex geometries. Results We introduce CrimeRank, a learning to rank boosting algorithm for determining a crime hotspot map that directly optimizes the percentage of crime captured by the top ranked hotspots. The method employs a floating grid combined with a greedy hotspot selection algorithm for accurately capturing spatial risk in complex geometries. We illustrate the performance using crime and traffic incident data provided by the Indianapolis Metropolitan Police Department, IED attacks in Iraq, and data from the 2017 NIJ Real-time crime forecasting challenge. Conclusion Our learning to rank strategy was the top performing solution (PAI metric) in the 2017 challenge. We show that CrimeRank achieves even greater gains when the competition rules are relaxed by removing the constraint that grid cells be a regular tessellation.
背景犯罪、交通事故、恐怖袭击和其他时空随机事件在空间和时间上分布不均。就犯罪而言,热点和其他前瞻性警务计划旨在将有限的资源集中用于城市中风险最高的犯罪和社会危害热点。实施这些战略的关键步骤是构建用于对空间热点进行排序的评分模型。虽然这些方法是通过区域归一化 Recall@k(称为预测准确性指数)来评估的,但模型通常是通过最大似然法或经验法则来训练的,而这些法则可能不会优先考虑前 k 个热点的模型准确性。此外,目前的算法是在固定网格上定义的,无法捕捉到发生在社区和具有复杂几何形状的道路网络上的风险模式。结果 我们介绍了犯罪排名(CrimeRank),这是一种用于确定犯罪热点地图的学习排名提升算法,可直接优化排名靠前的热点所占的犯罪比例。该方法采用浮动网格与贪婪热点选择算法相结合的方式,可准确捕捉复杂几何图形中的空间风险。我们使用印第安纳波利斯大都会警察局提供的犯罪和交通事故数据、伊拉克的简易爆炸装置袭击以及 2017 年 NIJ 实时犯罪预测挑战赛的数据来说明该方法的性能。结论 我们的学习排名策略是 2017 年挑战赛中表现最佳的解决方案(PAI 指标)。我们的研究表明,如果通过取消网格单元必须是规则细分网格的限制来放宽竞赛规则,CrimeRank 将获得更大的收益。
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引用次数: 0
Constellations of youth criminogenic factors associated with young adult violent criminal behavior 与青少年暴力犯罪行为相关的青少年犯罪诱因组合
IF 6.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-01-30 DOI: 10.1186/s40163-020-0111-2
Menno Segeren, Thijs Fassaert, Matty de Wit, Arne Popma
This study identified constellations of childhood risk factors associated with violent criminal behavior in early adulthood. Police data were used to sample violent and nonviolent offenders from a population of young adult males with a history of juvenile probation. Risk factors were retrieved from their juvenile probation files. A single classification tree analysis organized these into a decision tree for violent criminal behavior with good predictive accuracy. Two constellations of risk factors were associated with a high risk of violent criminal behavior. The first consisted of juvenile delinquents who had been moderately involved with criminal peers, who had committed offenses under the influence of drugs, and who came from a dysfunctional family. The second was characterized by having been severely involved with criminal peers and having had criminal family members. Presenting with depressive symptoms in childhood was associated with a low risk of violent criminal behavior. These constellations bear clinical importance as they provide targets for personalized interventions.
本研究确定了与成年早期暴力犯罪行为相关的童年风险因素组合。研究利用警方数据,从有少年缓刑史的年轻成年男性中抽取暴力犯罪者和非暴力犯罪者样本。风险因素是从他们的青少年缓刑档案中提取的。通过单一的分类树分析,将这些因素归纳到一个具有良好预测准确性的暴力犯罪行为决策树中。有两种风险因素组合与暴力犯罪行为的高风险相关。第一种是与犯罪同龄人有中度交往、在毒品影响下犯罪以及来自不健全家庭的少年犯。第二类少年犯的特点是与犯罪同龄人有严重的牵连,其家庭成员也有犯罪行为。童年时期出现抑郁症状与暴力犯罪行为的低风险相关。这些组合具有重要的临床意义,因为它们为个性化干预提供了目标。
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引用次数: 0
What is security worth to consumers? Investigating willingness to pay for secure Internet of Things devices 安全对消费者来说值多少钱?调查安全物联网设备的支付意愿
IF 6.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-01-08 DOI: 10.1186/s40163-019-0110-3
John M. Blythe, Shane D. Johnson, Matthew Manning
The Internet of Things (IoT) is considered the next technological revolution. IoT devices include once everyday objects that are now internet connected, such as smart locks and smart fridges, but also new types of devices to include home assistants. However, while this increased interconnectivity brings considerable benefits, it can and does increase people’s exposure to crime risk. This is particularly the case as most devices are developed without security in mind. One reason for this is that there is little incentive for manufacturers to make devices secure by design, and the costs of so doing do not encourage it. The principle aim of the current paper was to estimate the extent to which consumers are willing to pay for improved security in internet connected products. The second aim was to examine whether this is conditioned by their exposure to security-related information. Using an experimental design, and a contingent valuation method, we find that people are willing to pay for improved security and that for some devices, this increases if they are exposed to information about security prior to stating their willingness to pay. The implications of our findings for industry and the secure by design agenda are discussed.
物联网(IoT)被认为是下一场技术革命。物联网设备包括曾经与互联网连接的日常用品,如智能锁和智能冰箱,也包括家庭助理等新型设备。然而,虽然这种互联性的增强带来了相当大的好处,但它可能也确实增加了人们面临的犯罪风险。尤其是大多数设备在开发时都没有考虑到安全问题。造成这种情况的一个原因是,制造商没有什么动力在设计上保证设备的安全性,而且这样做的成本也不高。本文的主要目的是估算消费者在多大程度上愿意为提高联网产品的安全性付费。第二个目的是研究消费者是否会因接触安全相关信息而产生付费意愿。通过实验设计和或然估价法,我们发现人们愿意为改进的安全性付费,而且对于某些设备,如果他们在表示付费意愿之前接触过有关安全性的信息,付费意愿就会增加。本文讨论了我们的发现对行业和安全设计议程的影响。
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引用次数: 0
Somehow I always end up alone: COVID-19, social isolation and crime in Queensland, Australia. 不知何故,我总是孤独终老:在澳大利亚昆士兰州,COVID-19、社会隔离和犯罪。
IF 6.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-01-01 Epub Date: 2020-11-24 DOI: 10.1186/s40163-020-00135-4
Martin A Andresen, Tarah Hodgkinson

The COVID-19 pandemic has dramatically affected social life. In efforts to reduce the spread of the virus, countries around the world implemented social restrictions, including social distancing, working from home, and the shuttering of numerous businesses. These social restrictions have also affected crime rates. In this study, we investigate the impact of the COVID-19 pandemic on the frequency of offending (crimes include property, violent, mischief, and miscellaneous) in Queensland, Australia. In particular, we examine this impact across numerous settings, including rural, regional and urban. We measure these shifts across the restriction period, as well as the staged relaxation of these restrictions. In order to measure impact of this period we use structural break tests. In general, we find that criminal offences have significantly decreased during the initial lockdown, but as expected, increased once social restrictions were relaxed. These findings were consistent across Queensland's districts, save for two areas. We discuss how these findings are important for criminal justice and social service practitioners when operating within an extraordinary event.

新冠肺炎疫情严重影响社会生活。为了减少病毒的传播,世界各国实施了社会限制措施,包括保持社交距离、在家工作和关闭大量企业。这些社会限制也影响了犯罪率。在这项研究中,我们调查了2019冠状病毒病大流行对澳大利亚昆士兰州犯罪频率的影响(犯罪包括财产、暴力、恶作剧和杂项)。我们特别研究了包括农村、区域和城市在内的许多环境中的这种影响。我们衡量了整个限制期间的这些变化,以及这些限制的阶段性放松。为了测量这一时期的影响,我们使用结构断裂试验。总体而言,我们发现,在最初的封锁期间,刑事犯罪明显减少,但正如预期的那样,一旦放松社会限制,刑事犯罪就会增加。除了两个地区外,这些发现在昆士兰州的各个地区都是一致的。我们将讨论这些发现对刑事司法和社会服务从业者在特殊事件中运作的重要性。
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引用次数: 40
Crime and coronavirus: social distancing, lockdown, and the mobility elasticity of crime. 犯罪和冠状病毒:社交距离、封锁和犯罪的流动性弹性。
IF 6.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-01-01 Epub Date: 2020-07-06 DOI: 10.1186/s40163-020-00121-w
Eric Halford, Anthony Dixon, Graham Farrell, Nicolas Malleson, Nick Tilley

Governments around the world restricted movement of people, using social distancing and lockdowns, to help stem the global coronavirus (COVID-19) pandemic. We examine crime effects for one UK police force area in comparison to 5-year averages. There is variation in the onset of change by crime type, some declining from the WHO 'global pandemic' announcement of 11 March, others later. By 1 week after the 23 March lockdown, all recorded crime had declined 41%, with variation: shoplifting (- 62%), theft (- 52%), domestic abuse (- 45%), theft from vehicle (- 43%), assault (- 36%), burglary dwelling (- 25%) and burglary non-dwelling (- 25%). We use Google Covid-19 Community Mobility Reports to calculate the mobility elasticity of crime for four crime types, finding shoplifting and other theft inelastic but responsive to reduced retail sector mobility (MEC = 0.84, 0.71 respectively), burglary dwelling elastic to increases in residential area mobility (- 1), with assault inelastic but responsive to reduced workplace mobility (0.56). We theorise that crime rate changes were primarily caused by those in mobility, suggesting a mobility theory of crime change in the pandemic. We identify implications for crime theory, policy and future research.

世界各国政府通过保持社交距离和封锁来限制人员流动,以帮助遏制全球冠状病毒(COVID-19)大流行。我们将一个英国警察部队区域的犯罪影响与5年平均值进行比较。不同犯罪类型发生变化的时间有所不同,一些犯罪类型在世卫组织3月11日宣布“全球大流行”后有所下降,另一些犯罪类型则有所下降。截至3月23日封锁后一周,所有记录在案的犯罪下降了41%,各有不同:入店行窃(- 62%)、盗窃(- 52%)、家庭暴力(- 45%)、车辆盗窃(- 43%)、袭击(- 36%)、入室盗窃(- 25%)和入室盗窃(- 25%)。我们使用谷歌Covid-19社区流动性报告来计算四种犯罪类型的犯罪流动性弹性,发现入店行窃和其他盗窃无弹性,但对零售业流动性减少有反应(MEC分别= 0.84和0.71),入室行窃对住宅区流动性增加有弹性(- 1),袭击无弹性,但对工作场所流动性减少有反应(0.56)。我们的理论认为犯罪率的变化主要是由流动性引起的,这提出了大流行中犯罪变化的流动性理论。我们确定了对犯罪理论、政策和未来研究的影响。
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引用次数: 4
Disentangling community-level changes in crime trends during the COVID-19 pandemic in Chicago. 解开芝加哥COVID-19大流行期间社区层面犯罪趋势的变化。
IF 6.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-01-01 Epub Date: 2020-10-27 DOI: 10.1186/s40163-020-00131-8
Gian Maria Campedelli, Serena Favarin, Alberto Aziani, Alex R Piquero

Recent studies exploiting city-level time series have shown that, around the world, several crimes declined after COVID-19 containment policies have been put in place. Using data at the community-level in Chicago, this work aims to advance our understanding on how public interventions affected criminal activities at a finer spatial scale. The analysis relies on a two-step methodology. First, it estimates the community-wise causal impact of social distancing and shelter-in-place policies adopted in Chicago via Structural Bayesian Time-Series across four crime categories (i.e., burglary, assault, narcotics-related offenses, and robbery). Once the models detected the direction, magnitude and significance of the trend changes, Firth's Logistic Regression is used to investigate the factors associated to the statistically significant crime reduction found in the first step of the analyses. Statistical results first show that changes in crime trends differ across communities and crime types. This suggests that beyond the results of aggregate models lies a complex picture characterized by diverging patterns. Second, regression models provide mixed findings regarding the correlates associated with significant crime reduction: several relations have opposite directions across crimes with population being the only factor that is stably and positively associated with significant crime reduction.

最近利用城市时间序列进行的研究表明,在全球范围内,在COVID-19遏制政策实施后,有几种犯罪有所下降。利用芝加哥社区层面的数据,这项工作旨在促进我们对公共干预如何在更精细的空间尺度上影响犯罪活动的理解。该分析依赖于两步方法。首先,它通过结构贝叶斯时间序列估计了芝加哥采用的社会距离和庇护政策对社区的因果影响,这些政策涉及四种犯罪类别(即入室盗窃、袭击、毒品相关犯罪和抢劫)。一旦模型检测到趋势变化的方向、幅度和重要性,Firth的逻辑回归就被用来调查与第一步分析中发现的统计上显著的犯罪减少有关的因素。统计结果首先表明,不同社区和犯罪类型的犯罪趋势的变化有所不同。这表明,在综合模型的结果之外,存在着一个以发散模式为特征的复杂图景。其次,回归模型提供了与显著减少犯罪相关的混合结果:几种关系在犯罪之间具有相反的方向,人口是唯一与显著减少犯罪稳定和积极相关的因素。
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引用次数: 85
"Show this thread": policing, disruption and mobilisation through Twitter. An analysis of UK law enforcement tweeting practices during the Covid-19 pandemic. "展示这条线索":通过推特维持治安、破坏和动员。对 Covid-19 大流行期间英国执法部门推特实践的分析。
IF 3.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-01-01 Epub Date: 2020-10-21 DOI: 10.1186/s40163-020-00129-2
Manja Nikolovska, Shane D Johnson, Paul Ekblom

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.

危机和混乱往往是不可预测的,并可能为犯罪创造机会。在此期间,警务工作可能还需要应对更多挑战,以处理混乱局面。官员使用社交媒体对于缓解危机和减少犯罪至关重要。在本文中,我们研究了英国警方(及相关)机构在 Covid-19 大流行初期使用 Twitter 来缓解和减少犯罪的情况。我们的研究结果表明,虽然我们样本中的大多数推文涉及的问题并不特别与犯罪有关,尤其是在大流行病的初期阶段,但有关欺诈、网络犯罪和家庭虐待的推文显著增加。与原创信息相比,转发活动也有所增加。此外,就推文的影响而言(以推文的转发率衡量),如果推文内容丰富(讨论特定犯罪问题并包含媒体),追随者就更有可能 "传播消息",而且账户持有人本身在推特上也更加活跃。考虑到我们生活的世界在不断变化,犯罪机会很可能会不断演变。为帮助缓解这一问题,政策制定者和研究人员应考虑采用更系统的方法来制定社交媒体传播战略,以便在更广泛的混乱和变化中减轻和减少犯罪。我们为此提出了一个框架。
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引用次数: 0
Routine activity effects of the Covid-19 pandemic on burglary in Detroit, March, 2020. 2020 年 3 月,Covid-19 大流行对底特律入室盗窃的常规活动影响。
IF 6.1 Q1 CRIMINOLOGY & PENOLOGY Pub Date : 2020-01-01 Epub Date: 2020-06-23 DOI: 10.1186/s40163-020-00120-x
Marcus Felson, Shanhe Jiang, Yanqing Xu

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.

冠状病毒的传播导致许多地方采取了遏制政策,日常活动也随之改变。据报道,犯罪率因此大幅下降。然而,犯罪率的下降取决于犯罪类型,而且可能因城市的不同地区和土地用途而异。本文研究了密歇根州底特律市 2020 年 3 月期间的入室盗窃案件,这一时期的日常活动发生了很大变化。我们研究了 879 个街区组,将以住宅用地为主的街区组与土地利用较为混合的街区组分开。我们将该月分为三个时期:管制前、过渡期和管制后。在土地混合使用的街区组中,入室盗窃案有所增加,而以住宅用地为主的街区组中,入室盗窃案则没有增加。在考虑了土地用途之后,遏制政策对入室盗窃的影响更加明确。
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引用次数: 0
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Crime Science
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