Rating places and crime prevention: Exploring user-generated ratings to assess place management

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES Computers Environment and Urban Systems Pub Date : 2024-02-23 DOI:10.1016/j.compenvurbsys.2024.102088

Thom Snaphaan , Wim Hardyns , Lieven J.R. Pauwels , Kate Bowers

{"title":"Rating places and crime prevention: Exploring user-generated ratings to assess place management","authors":"Thom Snaphaan , Wim Hardyns , Lieven J.R. Pauwels , Kate Bowers","doi":"10.1016/j.compenvurbsys.2024.102088","DOIUrl":null,"url":null,"abstract":"<div><p>This study assesses how the quality of place management (measured with user-generated ratings from Google Places) is related to crime occurrences at specific settings and whether specific crime types are related to specific types of places. In 50 randomly sampled neighborhoods in Ghent (Belgium) and London (United Kingdom), we analyzed Google Places data as a proxy measure for the quality of place management at the street segment level. We used hurdle models to examine the effects for both the prevalence and frequency of crime at micro places, and to deal with excess zeros in the data. User-generated ratings of places provide a useful place-level indicator for place management that are related to crime. However, contextual differences are found between Ghent and London. For London, the results suggest that higher quality of place management has a protective effect on crime occurrences at the street segment level. This study indicates the importance of exploring new and emerging data sources as unique measurement opportunities to enhance insight in crime prevention mechanisms, and also acknowledges its limitations. For the first time from a large-scale empirical perspective, this study suggest that improving place management at specific places might be an effective intervention to guard against crime.</p></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"109 ","pages":"Article 102088"},"PeriodicalIF":7.1000,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers Environment and Urban Systems","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0198971524000176","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}

引用次数: 0

Abstract

This study assesses how the quality of place management (measured with user-generated ratings from Google Places) is related to crime occurrences at specific settings and whether specific crime types are related to specific types of places. In 50 randomly sampled neighborhoods in Ghent (Belgium) and London (United Kingdom), we analyzed Google Places data as a proxy measure for the quality of place management at the street segment level. We used hurdle models to examine the effects for both the prevalence and frequency of crime at micro places, and to deal with excess zeros in the data. User-generated ratings of places provide a useful place-level indicator for place management that are related to crime. However, contextual differences are found between Ghent and London. For London, the results suggest that higher quality of place management has a protective effect on crime occurrences at the street segment level. This study indicates the importance of exploring new and emerging data sources as unique measurement opportunities to enhance insight in crime prevention mechanisms, and also acknowledges its limitations. For the first time from a large-scale empirical perspective, this study suggest that improving place management at specific places might be an effective intervention to guard against crime.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

场所评级与预防犯罪：探索通过用户生成的评级来评估场所管理

本研究评估了场所管理质量（通过谷歌场所的用户评分来衡量）与特定场所的犯罪发生率之间的关系，以及特定犯罪类型是否与特定类型的场所有关。在根特（比利时）和伦敦（英国）随机抽取的 50 个社区中，我们分析了 Google Places 数据，将其作为街道层面场所管理质量的替代衡量标准。我们使用阶跃模型来检验微观场所犯罪率和频率的影响，并处理数据中多余的零。用户对场所的评分为与犯罪有关的场所管理提供了一个有用的场所级指标。不过，根特和伦敦的情况有所不同。伦敦的研究结果表明，较高的场所管理质量对街道层面的犯罪率具有保护作用。这项研究表明了探索新兴数据源作为独特测量机会的重要性，以提高对犯罪预防机制的洞察力，同时也承认了其局限性。本研究首次从大规模实证的角度提出，改善特定场所的场所管理可能是防范犯罪的有效干预措施。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Computers Environment and Urban Systems Multiple-

CiteScore

13.30

自引率

7.40%

发文量

111

审稿时长

32 days

期刊介绍： Computers, Environment and Urban Systemsis an interdisciplinary journal publishing cutting-edge and innovative computer-based research on environmental and urban systems, that privileges the geospatial perspective. The journal welcomes original high quality scholarship of a theoretical, applied or technological nature, and provides a stimulating presentation of perspectives, research developments, overviews of important new technologies and uses of major computational, information-based, and visualization innovations. Applied and theoretical contributions demonstrate the scope of computer-based analysis fostering a better understanding of environmental and urban systems, their spatial scope and their dynamics.