Objectives: Building on Hägerstrand’s time geography, we expect temporal consistency in individual offending behavior. We hypothesize that repeat offenders commit offenses at similar times of day and week. In addition, we expect stronger temporal …
We illustrate how a machine learning algorithm, Random Forests, can provide accurate long-term predictions of crime at micro places relative to other popular techniques. We also show how recent advances in model summaries can help to open the ‘black …
The analysis of geographically referenced data, specifically point data, is predicated on the accurate geocoding of those data. Geocoding refers to the process in which geographically referenced data (addresses, for example) are placed on a map. This …
Account hijacking, i.e. illegitimately accessing someone else’s personal online account, is on the rise and affects not only financial accounts, but the full spectrum of online accounts. To gain more insight in the illicit act of online dissemination …
Background: A key issue in the analysis of many spatial processes is the choice of an appropriate scale for the analysis. Smaller geographical units are generally preferable for the study of human phenomena because they are less likely to cause …
Objectives: To examine the spatial concentration and spatial stability of residential burglary at micro places in the context of a substantial city-level burglary drop in Antwerp, Belgium. Methods: 51,337 police recorded home burglary incidents for …
Objectives: The present study focuses on Systematic Social Observation (SSO) as a method to investigate physical and social disorder at different units of analysis. The study contributes to the aggregation bias debate and to the ‘social science of …
Andresen's spatial point pattern test (SPPT) compares two spatial point patterns on defined areal units; it identifies areas where the spatial point patterns diverge and aggregates these local (dis)similarities to one global measure. We discuss the …