{"title":"冠状病毒大流行中的反社会行为。","authors":"Eric Halford, Anthony Dixon, Graham Farrell","doi":"10.1186/s40163-022-00168-x","DOIUrl":null,"url":null,"abstract":"<p><p>Anti-social behaviour recorded by police more than doubled early in the coronavirus pandemic in England and Wales. This was a stark contrast to the steep falls in most types of recorded crime. Why was ASB so different? Was it changes in 'traditional' ASB such as noisy neighbours, or was it ASB records of breaches of COVID-19 regulations? Further, why did police-recorded ASB find much larger early-pandemic increases than the Telephone Crime Survey for England and Wales? This study uses two approaches to address the issues. The first is a survey of police forces, via Freedom of Information requests, to determine whether COVID-regulation breaches were recorded as ASB. The second is natural language processing (NLP) used to interrogate the text details of police ASB records. We find police recording practice varied greatly between areas. We conclude that the early-pandemic increases in recorded ASB were primarily due to breaches of COVID regulations but around half of these also involved traditional forms of ASB. We also suggest that the study offers proof of concept that NLP may have significant general potential to exploit untapped police text records in ways that inform policing and crime policy.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9251022/pdf/","citationCount":"0","resultStr":"{\"title\":\"Anti-social behaviour in the coronavirus pandemic.\",\"authors\":\"Eric Halford, Anthony Dixon, Graham Farrell\",\"doi\":\"10.1186/s40163-022-00168-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Anti-social behaviour recorded by police more than doubled early in the coronavirus pandemic in England and Wales. This was a stark contrast to the steep falls in most types of recorded crime. Why was ASB so different? Was it changes in 'traditional' ASB such as noisy neighbours, or was it ASB records of breaches of COVID-19 regulations? Further, why did police-recorded ASB find much larger early-pandemic increases than the Telephone Crime Survey for England and Wales? This study uses two approaches to address the issues. The first is a survey of police forces, via Freedom of Information requests, to determine whether COVID-regulation breaches were recorded as ASB. The second is natural language processing (NLP) used to interrogate the text details of police ASB records. We find police recording practice varied greatly between areas. We conclude that the early-pandemic increases in recorded ASB were primarily due to breaches of COVID regulations but around half of these also involved traditional forms of ASB. We also suggest that the study offers proof of concept that NLP may have significant general potential to exploit untapped police text records in ways that inform policing and crime policy.</p>\",\"PeriodicalId\":37844,\"journal\":{\"name\":\"Crime Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9251022/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Crime Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s40163-022-00168-x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/7/4 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CRIMINOLOGY & PENOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Crime Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s40163-022-00168-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/7/4 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CRIMINOLOGY & PENOLOGY","Score":null,"Total":0}
Anti-social behaviour in the coronavirus pandemic.
Anti-social behaviour recorded by police more than doubled early in the coronavirus pandemic in England and Wales. This was a stark contrast to the steep falls in most types of recorded crime. Why was ASB so different? Was it changes in 'traditional' ASB such as noisy neighbours, or was it ASB records of breaches of COVID-19 regulations? Further, why did police-recorded ASB find much larger early-pandemic increases than the Telephone Crime Survey for England and Wales? This study uses two approaches to address the issues. The first is a survey of police forces, via Freedom of Information requests, to determine whether COVID-regulation breaches were recorded as ASB. The second is natural language processing (NLP) used to interrogate the text details of police ASB records. We find police recording practice varied greatly between areas. We conclude that the early-pandemic increases in recorded ASB were primarily due to breaches of COVID regulations but around half of these also involved traditional forms of ASB. We also suggest that the study offers proof of concept that NLP may have significant general potential to exploit untapped police text records in ways that inform policing and crime policy.
期刊介绍:
Crime Science is an international, interdisciplinary, peer-reviewed journal with an applied focus. The journal''s main focus is on research articles and systematic reviews that reflect the growing cooperation among a variety of fields, including environmental criminology, economics, engineering, geography, public health, psychology, statistics and urban planning, on improving the detection, prevention and understanding of crime and disorder. Crime Science will publish theoretical articles that are relevant to the field, for example, approaches that integrate theories from different disciplines. The goal of the journal is to broaden the scientific base for the understanding, analysis and control of crime and disorder. It is aimed at researchers, practitioners and policy-makers with an interest in crime reduction. It will also publish short contributions on timely topics including crime patterns, technological advances for detection and prevention, and analytical techniques, and on the crime reduction applications of research from a wide range of fields. Crime Science publishes research articles, systematic reviews, short contributions and theoretical articles. While Crime Science uses the APA reference style, the journal welcomes submissions using alternative reference styles on a case-by-case basis.