Measuring Neighborhood Connectivity and Racial Homophily in Urban Encounter Networks: Insights from Mobile Phone Location Data

Keywords: urban encounters, network analysis, mobile phone location data, segregation, neighborhood
Abstract Type: Paper Abstract

Abstract

Urban encounters, defined as the co-presence of individuals in shared physical spaces, create opportunities for social interaction, playing a key role in building social networks and fostering social integration. This study uses three months of mobile phone GPS data from Charlotte, North Carolina, to construct a neighborhood-based network through the lens of urban encounters. The research has two primary objectives: (1) to analyze both the global and local structures of the encounter network using multi-scale complex network analysis, and (2) to examine the relationship between neighborhood characteristics, neighborhood connectivity, and racial homophily. The global analysis reveals that the neighborhood-based encounter network is highly connected and cohesive, with significant racial homophily (segregation), particularly among white and black residents. Meanwhile, the local analysis uncovers considerable variation in connectivity and racial homophily within activity spaces across neighborhoods. By applying the Kernel Regularized Least Squares (KRLS) model, the study further disentangles the role of neighborhood characteristics in shaping local network structures, including degree centrality and local assortativity. The results indicate that neighborhood connectivity and segregation level is significantly influenced by their demographic and socioeconomic profiles. Younger and wealthier neighborhoods, as well as those with higher levels of education and employment, are more likely to establish connections with other neighborhoods. Additionally, social infrastructures also demonstrate significant roles in enhancing social interaction potential between neighborhoods and racial groups.