  Emerging research suggests that the extent to which activity spaces -- the
collection of an individual's routine activity locations -- overlap provides
important information about the functioning of a city and its neighborhoods. To
study patterns of overlapping activity spaces, we draw on the notion of an
ecological network, a type of two-mode network with the two modes being
individuals and the geographic locations where individuals perform routine
activities. We describe a method for detecting "ecological communities" within
these networks based on shared activity locations among individuals.
Specifically, we identify latent activity pattern profiles, which, for each
community, summarize its members' probability distribution of going to each
location, and community assignment vectors, which, for each individual,
summarize his/her probability distribution of belonging to each community.
Using data from the Adolescent Health and Development in Context (AHDC) Study,
we employ latent Dirichlet allocation (LDA) to identify activity pattern
profiles and communities. We then explore differences across neighborhoods in
the strength, and within-neighborhood consistency of community assignment. We
hypothesize that these aspects of the neighborhood structure of ecological
community membership capture meaningful dimensions of neighborhood functioning
likely to co-vary with economic and racial composition. We discuss the
implications of a focus on ecological communities for the conduct of
"neighborhood effects" research more broadly.
