Routine Activities Analysis for Crime Prediction

Project Overview

This project focuses on the spatiotemporal prediction of localized attacks carried out against individuals in urban areas. We view an attack as the outcome of a point process governed by the interaction of attackers, targets, and the physical environment. Our ultimate goal is to predict future outcomes of this process in order to increase the security of human populations and U.S. assets and interests. However, achieving this goal requires a deeper understanding of how attack outcomes correlate with the routine activities of individuals in an area. The proposed research will generate this understanding and in doing so will answer questions such as the following: What are the dimensions along which individuals’ activities should be quantified for the purpose of attack prediction? How can measurements along these dimensions be taken automatically and with minimal expense (e.g., via social media)? What are the implications of such measurements for attack prediction performance? Subsuming these questions is the issue of geographic variation: do our answers change when moving from a major U.S. city to a major U.K. city? There has been plenty of previous work on spatiotemporal attack prediction (see our Asymmetric Threat project); however, these basic questions remain unanswered, leaving a substantial gap in our understanding of attack processes and their relationships with individuals’ routine activities. [1]

We are looking for highly ambitious graduate students to collaborate with us on this project. Please get in touch if you are interested.