UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

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

Snaphaan, T; Hardyns, W; Pauwels, LJR; Bowers, K; (2024) Rating places and crime prevention: Exploring user-generated ratings to assess place management. Computers, Environment and Urban Systems , 109 , Article 102088. 10.1016/j.compenvurbsys.2024.102088.

[thumbnail of 2024_A1_Snaphaan et al_Rating places and crime prevention_AAM.pdf] Text
2024_A1_Snaphaan et al_Rating places and crime prevention_AAM.pdf - Accepted Version
Access restricted to UCL open access staff until 24 August 2025.

Download (768kB)

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.

Type: Article
Title: Rating places and crime prevention: Exploring user-generated ratings to assess place management
DOI: 10.1016/j.compenvurbsys.2024.102088
Publisher version: http://dx.doi.org/10.1016/j.compenvurbsys.2024.102...
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Big data, Crime concentrations, Google Places, Place management, Situational crime prevention
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science
URI: https://discovery.ucl.ac.uk/id/eprint/10189598
Downloads since deposit
1Download
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item