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Exploring the usefulness of the INLA model in predicting levels of crime in the City of Johannesburg, South Africa 探索 INLA 模型在预测南非约翰内斯堡市犯罪水平方面的实用性
IF 6.1
Crime Science Pub Date : 2024-09-04 DOI: 10.1186/s40163-024-00219-5
Toshka Coleman, Paul Mokilane, Mapitsi Rangata, Jenny Holloway, Nicolene Botha, Renee Koen, Nontembeko Dudeni-Tlhone
{"title":"Exploring the usefulness of the INLA model in predicting levels of crime in the City of Johannesburg, South Africa","authors":"Toshka Coleman, Paul Mokilane, Mapitsi Rangata, Jenny Holloway, Nicolene Botha, Renee Koen, Nontembeko Dudeni-Tlhone","doi":"10.1186/s40163-024-00219-5","DOIUrl":"https://doi.org/10.1186/s40163-024-00219-5","url":null,"abstract":"<p>Crime prediction serves as a valuable tool for deriving insightful information that can inform policy decisions at both operational and strategic tiers. This information can be used to identify high-crime areas, and optimise resource allocation and personnel management for crime prevention. Traditionally, techniques such as the Poisson model and regression analysis have been widely used for crime prediction. However, recent statistical advancements have introduced Integrated Nested Laplace Approximations (INLA) as a promising alternative for spatial and temporal data analysis. This study focuses on crime prediction using the INLA model. Specifically, the first-order autoregressive model under the INLA modelling framework is employed on longitudinal data for crime predictions in different regions of the City of Johannesburg, South Africa. The model parameters and hyperparameters considering space and time are estimated through the INLA model. In this work, the suitability and performance of the INLA model for crime prediction is assessed, which effectively captures spatial and temporal patterns. This study contributes to research by first introducing a novel approach for South African crime prediction. Secondly, it develops a model using no demographic information other than clustering attributes as an exogenous variable. Thirdly, it quantifies prediction uncertainty. Finally, it addresses data scarcity through demonstrating how INLA can provide reliable crime predictions, where conventional methods are limited. Based on our findings, the INLA model ranked areas by crime levels, obtaining a 29.3% Mean Absolute Percentage Error (MAPE) and 0.8 <span>(R^2)</span> value for crime predictions. These findings and contributions presents the potential of INLA in advancing evidence-based decision-making for crime prevention.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142197734","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
Rapid assessment of human–elephant conflict: a crime science approach 快速评估人象冲突:犯罪学方法
IF 6.1
Crime Science Pub Date : 2024-09-03 DOI: 10.1186/s40163-024-00223-9
Mangai Natarajan
{"title":"Rapid assessment of human–elephant conflict: a crime science approach","authors":"Mangai Natarajan","doi":"10.1186/s40163-024-00223-9","DOIUrl":"https://doi.org/10.1186/s40163-024-00223-9","url":null,"abstract":"<p>An interdisciplinary approach has the potential not only to help solve conservation-centric problems but also to enrich and improve evidence-based scientific research. Crime science, an offshoot of criminology, provides a comprehensive, solution-oriented approach that transcends disciplinary boundaries and bridges science and practice for developing effective conservation interventions to real-life problems such as Human Elephant Conflict (HEC). This paper focuses on HEC as a conservation concern, but the resultant behaviors toward elephants, people, and their property are criminology’s concern. Using the Action Research paradigm, a rapid assessment of human–elephant conflict (HEC) in India was undertaken to identify contextual solutions. This study utilized problem-oriented field research methods that enabled the gathering of data on elephant habitat-landscape, villagers’ lifestyle (habitat) in the fringe areas, their current approaches in dealing with the conflict, the challenges forest officials face to mitigate HEC, and the assistance provided by district administrators to protect villagers and their corps and HEC-related deaths. The qualitative inquiry, including observation of village-forest fringe areas, focus group discussions with villagers, and interviews with forest officers and rangers, and district administrators/collectors who are handlers, guardians, and managers of the conflict space, provided rich data in identifying situational practical measures and underscored the role of crime science in providing a conceptual framework to gather evidence in addressing HEC in forest areas. The findings of the research suggest that human–animal convergence space is the source (or location) of conflict and criminology-driven situational crime prevention measures, including increasing effort, risks, reducing rewards and provocations, and removing excuses might mitigate the conflict, requiring coordinated efforts by villagers, forest and district administrators, and local law enforcers.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142197735","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
The heterogeneous effects of COVID-19 lockdowns on crime across the world COVID-19 封锁对世界各地犯罪的不同影响
IF 6.1
Crime Science Pub Date : 2024-08-22 DOI: 10.1186/s40163-024-00220-y
N. Trajtenberg, S. Fossati, C. Diaz, A. E. Nivette, R. Aguilar, A. Ahven, L. Andrade, S. Amram, B. Ariel, M. J. Arosemena Burbano, R. Astolfi, D. Baier, H.-M. Bark, J. E. H. Beijers, M. Bergman, D. Borges, G. Breeztke, I. Cano, I. A. Concha Eastman, S. Curtis-Ham, R. Davenport, C. Droppelman, D. Fleitas, M. Gerell, K.-H. Jang, J. Kääriäinen, T. Lappi-Seppälä, W.-S. Lim, R. Loureiro Revilla, L. Mazerolle, C. Mendoza, G. Meško, N. Pereda, M. F. Peres, R. Poblete-Cazenave, E. Rojido, S. Rose, O. Sanchez de Ribera, R. Svensson, T. van der Lippe, J. A. M. Veldkamp, C. J. Vilalta Perdomo, R. Zahnow, M. P. Eisner
{"title":"The heterogeneous effects of COVID-19 lockdowns on crime across the world","authors":"N. Trajtenberg, S. Fossati, C. Diaz, A. E. Nivette, R. Aguilar, A. Ahven, L. Andrade, S. Amram, B. Ariel, M. J. Arosemena Burbano, R. Astolfi, D. Baier, H.-M. Bark, J. E. H. Beijers, M. Bergman, D. Borges, G. Breeztke, I. Cano, I. A. Concha Eastman, S. Curtis-Ham, R. Davenport, C. Droppelman, D. Fleitas, M. Gerell, K.-H. Jang, J. Kääriäinen, T. Lappi-Seppälä, W.-S. Lim, R. Loureiro Revilla, L. Mazerolle, C. Mendoza, G. Meško, N. Pereda, M. F. Peres, R. Poblete-Cazenave, E. Rojido, S. Rose, O. Sanchez de Ribera, R. Svensson, T. van der Lippe, J. A. M. Veldkamp, C. J. Vilalta Perdomo, R. Zahnow, M. P. Eisner","doi":"10.1186/s40163-024-00220-y","DOIUrl":"https://doi.org/10.1186/s40163-024-00220-y","url":null,"abstract":"<p>There is a vast literature evaluating the empirical association between stay-at-home policies and crime during the COVID-19 pandemic. However, these academic efforts have primarily focused on the effects within specific cities or regions rather than adopting a cross-national comparative approach. Moreover, this body of literature not only generally lacks causal estimates but also has overlooked possible heterogeneities across different levels of stringency in mobility restrictions. This paper exploits the spatial and temporal variation of government responses to the pandemic in 45 cities across five continents to identify the causal impact of strict lockdown policies on the number of offenses reported to local police. We find that cities that implemented strict lockdowns experienced larger declines in some crime types (robbery, burglary, vehicle theft) but not others (assault, theft, homicide). This decline in crime rates attributed to more stringent policy responses represents only a small proportion of the effects documented in the literature.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142197750","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
Understanding the role of mobility in the recorded levels of violent crimes during COVID-19 pandemic: a case study of Tamil Nadu, India 了解流动性在 COVID-19 大流行期间记录的暴力犯罪水平中的作用:印度泰米尔纳德邦案例研究
IF 6.1
Crime Science Pub Date : 2024-08-14 DOI: 10.1186/s40163-024-00222-w
Kandaswamy Paramasivan, Saish Jaiswal, Rahul Subburaj, Nandan Sudarsanam
{"title":"Understanding the role of mobility in the recorded levels of violent crimes during COVID-19 pandemic: a case study of Tamil Nadu, India","authors":"Kandaswamy Paramasivan, Saish Jaiswal, Rahul Subburaj, Nandan Sudarsanam","doi":"10.1186/s40163-024-00222-w","DOIUrl":"https://doi.org/10.1186/s40163-024-00222-w","url":null,"abstract":"This research investigates the potential link between mobility and violent crimes in Tamil Nadu, India, using an empirical study centred on the COVID-19 pandemic waves (2020–2022). The goal is to understand how these events influenced crime, employing a counterfactual approach. The study employs the XGBoost algorithm to forecast counterfactual events across different timeframes with varying levels of mobility. The mobility data sources include historical bus and passenger records spanning a decade, along with Google Community Mobility Reports added during the pandemic phases. The foundation for crime analysis is built upon the univariate time series of violent crimes reported as First Information Reports from 2010 to 2022. Results indicate a significant correlation between mobility and violent crimes when mobility drops below a specific threshold. However, no such correlation is observed when mobility is above this threshold during the non-pandemic periods. The COVID-19 pandemic had a major impact on people’s and vehicular mobility, especially during the complete lockdown periods of the first two waves, and also affected crime rates. The decrease in recorded incidents could also be attributed to fewer criminal opportunities. Additionally, this could be due to unfavourable situational factors, such as victims’ limited access to appropriate health and law enforcement agencies to report crimes. Furthermore, frontline services were busy with pandemic-related commitments, which could have contributed to a lack of crime registration even when crimes were committed.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142197751","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
Shootings across the rural–urban continuum 跨越城乡的枪击事件
IF 6.1
Crime Science Pub Date : 2024-07-26 DOI: 10.1186/s40163-024-00217-7
Vania Ceccato, Patryk Mentel, Ned Levine, Manne Gerell
{"title":"Shootings across the rural–urban continuum","authors":"Vania Ceccato, Patryk Mentel, Ned Levine, Manne Gerell","doi":"10.1186/s40163-024-00217-7","DOIUrl":"https://doi.org/10.1186/s40163-024-00217-7","url":null,"abstract":"<p>In this article, we investigate situations involving firearm violence in Sweden. The spatiotemporal distribution of records is assessed in different contexts across the country and linked to land use, demographic, and socio-economic characteristics by area and by street segment. The findings emphasize the prevalence of evening shootings, particularly in economically disadvantaged areas where young people congregate in public places often in residential areas, in parks, in playgrounds, and in transit areas. Although two-thirds of shootings took place in larger urban municipalities, our study sheds light on the non-uniform distribution of gun violence along the rural–urban continuum. We conclude by offering suggestions for future research and practical interventions to address this pressing issue that negatively affects people and communities.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141772039","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
Modeling behavioral patterns of family violence aggressors 模拟家庭暴力施暴者的行为模式
IF 6.1
Crime Science Pub Date : 2024-07-23 DOI: 10.1186/s40163-024-00218-6
Apriel D. Jolliffe Simpson, Chaitanya Joshi, Devon L. L. Polaschek
{"title":"Modeling behavioral patterns of family violence aggressors","authors":"Apriel D. Jolliffe Simpson, Chaitanya Joshi, Devon L. L. Polaschek","doi":"10.1186/s40163-024-00218-6","DOIUrl":"https://doi.org/10.1186/s40163-024-00218-6","url":null,"abstract":"The presumption that family violence will repeat and escalate is embedded in practices including risk assessment and case management. However, there is limited evidence that further episodes are inevitable, or that subsequent episodes will increase in severity. Therefore, we need to better understand temporal patterns in aggressor behavior to inform how risk is conceptualized in practice. For a sample of 2115 family violence aggressors who came to police attention in Integrated Safety Response catchment areas in Aotearoa New Zealand, we collected information New Zealand Police routinely recorded about reported harm between 2018 and 2020. We used a hidden Markov model to estimate the latent (i.e., unmeasurable) states behind the information reported to police, and modeled aggressors’ movement between those states over time. We identified three latent states. The first contained low or no reported harm, the second contained low probabilities of reported harm, and the third involved a high probability of reported verbal abuse and a moderate probability of reported physical violence. We identified four pathways through the latent states over the two-year follow-up period, which we called No reported harm, High reported harm, Low reported harm, and De-escalation. The findings add to the body of research indicating that family violence aggressors do not inevitably repeat or escalate their harmful behavior, and that a small subset of cases account for a large proportion of reported harm. This study demonstrates how information that police routinely collect can be used to estimate aggressors’ latent behavioral states and model pathways communicating the probability that they will continue to come to police attention for family violence, contributing to improved risk assessment and practice.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141753992","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
The risk of negative feedback loops in some weighted measures of crime harm 某些犯罪危害性加权测量中的负反馈循环风险
IF 6.1
Crime Science Pub Date : 2024-06-27 DOI: 10.1186/s40163-024-00216-8
Sam Lewis, Jose Pina-Sánchez, Daniel Birks
{"title":"The risk of negative feedback loops in some weighted measures of crime harm","authors":"Sam Lewis, Jose Pina-Sánchez, Daniel Birks","doi":"10.1186/s40163-024-00216-8","DOIUrl":"https://doi.org/10.1186/s40163-024-00216-8","url":null,"abstract":"<p>Analyses of crime based upon aggregate counts of different crime types have restricted value, because they count all crime types equally irrespective of the harm caused. In response to this problem, a series of weighted measures of crime harm have been proposed. In this short contribution, we contend that the use of some crime harm metrics to inform police deployment practices has the potential to reinforce ethnic disparities in the criminal justice system through the creation of unintended negative feedback loops. We focus our analysis on the Cambridge Crime Harm Index and the Office for National Statistics (ONS) Crime Severity Score, the preeminent crime harm indexes in England and Wales. We conclude that the ONS Crime Severity Score, which is based on mean sentencing outcomes, <i>does</i> give cause for concern in some contexts. There is currently no evidence that the Cambridge Crime Harm Index, based on sentencing guidelines, presents the same problems.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141502152","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
The fight against disinformation and its consequences: measuring the impact of “Russia state-affiliated media” on Twitter 打击虚假信息及其后果:衡量 "俄罗斯国家附属媒体 "在推特上的影响
IF 6.1
Crime Science Pub Date : 2024-06-15 DOI: 10.1186/s40163-024-00215-9
Jesús-C. Aguerri, Mario Santisteban, F. Miró-Llinares
{"title":"The fight against disinformation and its consequences: measuring the impact of “Russia state-affiliated media” on Twitter","authors":"Jesús-C. Aguerri, Mario Santisteban, F. Miró-Llinares","doi":"10.1186/s40163-024-00215-9","DOIUrl":"https://doi.org/10.1186/s40163-024-00215-9","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141337777","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
Conti Inc.: understanding the internal discussions of a large ransomware-as-a-service operator with machine learning 康迪公司:利用机器学习了解大型勒索软件即服务运营商的内部讨论情况
IF 6.1
Crime Science Pub Date : 2024-06-12 DOI: 10.1186/s40163-024-00212-y
Estelle Ruellan, Masarah Paquet-Clouston, Sebastián Garcia
{"title":"Conti Inc.: understanding the internal discussions of a large ransomware-as-a-service operator with machine learning","authors":"Estelle Ruellan, Masarah Paquet-Clouston, Sebastián Garcia","doi":"10.1186/s40163-024-00212-y","DOIUrl":"https://doi.org/10.1186/s40163-024-00212-y","url":null,"abstract":"Ransomware-as-a-service (RaaS) is increasing the scale and complexity of ransomware attacks. Understanding the internal operations behind RaaS has been a challenge due to the illegality of such activities. The recent chat leak of the Conti RaaS operator, one of the most infamous ransomware operators on the international scene, offers a key opportunity to better understand the inner workings of such organizations. This paper analyzes the main discussion topics in the Conti chat leak using machine learning techniques such as Natural Language Processing (NLP) and Latent Dirichlet Allocation (LDA), as well as visualization strategies. Five discussion topics are found: (1) Business, (2) Technical, (3) Internal tasking/Management, (4) Malware, and (5) Customer Service/Problem Solving. Moreover, the distribution of topics among Conti members shows that only 4% of individuals have specialized discussions while almost all individuals (96%) are all-rounders, meaning that their discussions revolve around the five topics. The results also indicate that a significant proportion of Conti discussions are non-tech related. This study thus highlights that running such large RaaS operations requires a workforce skilled beyond technical abilities, with individuals involved in various tasks, from management to customer service or problem solving. The discussion topics also show that the organization behind the Conti RaaS operator shares similarities with a large firm. We conclude that, although RaaS represents an example of specialization in the cybercrime industry, only a few members are specialized in one topic, while the rest runs and coordinates the RaaS operation.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141502153","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
Understanding the impact of urban heat islands on crime: insights from temperature, population density, and green canopy cover 了解城市热岛对犯罪的影响:从温度、人口密度和绿色树冠覆盖率中获得的启示
IF 6.1
Crime Science Pub Date : 2024-06-06 DOI: 10.1186/s40163-024-00214-w
Emil E Jonescu, Chamil (Erik) Ramanayaka, O. Olatunji, Talia J. Uylaki
{"title":"Understanding the impact of urban heat islands on crime: insights from temperature, population density, and green canopy cover","authors":"Emil E Jonescu, Chamil (Erik) Ramanayaka, O. Olatunji, Talia J. Uylaki","doi":"10.1186/s40163-024-00214-w","DOIUrl":"https://doi.org/10.1186/s40163-024-00214-w","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379915","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
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