The text explores how location data can be used to identify and understand communities beyond traditional geographic boundaries, using Williamsburg, NY as a case study. The neighborhood's history of diverse immigrant communities, cultural tensions, and gentrification are considered in the context of modern urban mobility and spatial planning. A clustering algorithm called DBSCAN is applied to location data from taxi rides to group similar characteristics, such as pick-up and drop-off locations, day of the week, time of day, and trip distance. The resulting map reveals 75 communities, including "partiers", "intra-borough residents", "working class" residents, "visitors with expensive taste", and "Orthodox Jewish" residents, each with distinct patterns and behaviors.