In urban environments, social boundaries are the areas that emerge from processes of economic inequality and social segregation. These boundaries are important, as they serve both as areas of interaction and conflict. By applying geographical thinking to classic methods in data science, we can better understand where these boundaries emerge and how they delineate communities. In this talk, I’ll explain a bit about the basics of “boundary detection” in urban analytics. I’ll present a new method, the “geosilhouette,” that builds on previous methods of identifying the boundaries between clusters. And, finally, I’ll show how this can change our understanding of urban community.

Levi John Wolf is a Senior Lecturer in the School of Geographical Sciences at the University of Bristol and a Fellow with the Alan Turing Institute. He works on problems across social science, such as electoral district manipulation, segregation, sorting, and inequality, as well as developing novel statistical methods to interrogate them.