Recent decades have seen a rise in the use of physics methods to study different societal
phenomena. This development has been due to physicists venturing outside of their …

Self-exciting spatio-temporal point process models predict the rate of events as a function of
space, time, and the previous history of events. These models naturally capture triggering …

The concentration of police resources in stable crime hotspots has proven effective in
reducing crime, but the extent to which police can disrupt dynamically changing crime …

Highly clustered event sequences are observed in certain types of crime data, such as
burglary and gang violence, due to crime-specific patterns of criminal behavior. Similar …

Containing the spread of crime in urban societies remains a major challenge. Empirical
evidence suggests that, if left unchecked, crimes may be recurrent and proliferate. On the …

Objectives To test the generalizability of previous crime and place trajectory analysis
research on a different geographic location, Vancouver BC, and using alternative methods …

Objectives 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 …

There is much enthusiasm currently about the possibilities created by new and more
extensive sources of data to better understand and manage cities. Here, I explore how big …

Crime hotspot maps are a widely used and successful method of displaying spatial crime
patterns and allocating police resources. However, hotspot maps are often created over a …

The mechanisms driving the nucleation, spread, and dissipation of crime hotspots are poorly
understood. As a consequence, the ability of law enforcement agencies to use mapped …