Title: Community detection in co-location networks
Authors: Catherine Calder - University of Texas, Austin (United States) [presenting]
Abstract: The extent to which activity spaces - the collection of an individuals routine activity locations - overlap provides important information about the function of a city and its neighborhoods. To study the patterns of overlapping activity spaces and to detect communities of individuals based on their shared locations, we introduce the notion of an ecological network, a type of two-mode network with the two modes being individuals and routine activity locations. 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 Bayesian probabilistic topic models to identify activity pattern profiles and community assignment vectors. We then explore differences across neighborhoods of Columbus, OH in the strength, and within-neighborhood consistency of community assignment, paying particular attention to the association between race and these measures.