Association of violence with urban points of interest.

Joseph Redfern,Padraig Corcoran,Simon C Moore,Paul L Rosin,David Marshall,Kirill Sidorov,Shihe Fu

doi:10.1371/journal.pone.0239840

Abstract

The association between alcohol outlets and violence has long been recognised, and is commonly used to inform policing and licensing policies (such as staggered closing times and zoning). Less investigated, however, is the association between violent crime and other urban points of interest, which while associated with the city centre alcohol consumption economy, are not explicitly alcohol outlets. Here, machine learning (specifically, LASSO regression) is used to model the distribution of violent crime for the central 9 km2 of ten large UK cities. Densities of 620 different Point of Interest types (sourced from Ordnance Survey) are used as predictors, with the 10 most explanatory variables being automatically selected for each city. Cross validation is used to test generalisability of each model. Results show that the inclusion of additional point of interest types produces a more accurate model, with significant increases in performance over a baseline univariate alcohol-outlet only model. Analysis of chosen variables for city-specific models shows potential candidates for new strategies on a per-city basis, with combined-model variables showing the general trend in POI/violence association across the UK. Although alcohol outlets remain the best individual predictor of violence, other points of interest should also be considered when modelling the distribution of violence in city centres. The presented method could be used to develop targeted, city-specific initiatives that go beyond alcohol outlets and also consider other locations.

Highlights

There are many differing estimates as to the cost of alcohol-related crime to the police and health-care system, in the United Kingdom, it is widely accepted as being in the hundreds of millions of pounds per year [1]
We present an analysis of the relationship between various POI densities and levels of violent crime using machine-learning based approaches
We report the results averaged over all folds, with this procedure further repeated 100 times with different random splits. (A value of K = 2 was chosen so as to preserve enough points in the test set for reliable density estimation.) The same process was used for our baseline model

Summary

Introduction

There are many differing estimates as to the cost of alcohol-related crime to the police and health-care system, in the United Kingdom, it is widely accepted as being in the hundreds of millions of pounds per year [1]. In addition to the direct financial cost of alcohol related violence, there is a high societal cost—physical injuries sustained by victims can be life changing or fatal [2], the mental health of victims can be severely damaged [3], and reputations of cities can be permanently damaged [4]. Ac.uk/), and is available for evaluation under the Ordnance Survey data exploration license (https:// www.ordnancesurvey.co.uk/business-government/ licensing-agreements/data-exploration). The study used the "Points of Interest" product from via Digimap, as described here: https://digimap.edina.ac.uk/webhelp/os/ osdigimaphelp.htm#data_information/os_ products/points_of_interest.htm. The authors had no special access to Police.uk or Ordnance Survey data

Methods

Results

Conclusion