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Cities create potential for individuals from different backgrounds tointeract with one another. It is often the case, however, that urbaninfrastructure obfuscates this potential, creating dense pockets of affluenceand poverty throughout a region. The spatial distribution of job opportunities,and how it intersects with the residential landscape, is one of many suchobstacles. In this paper, we apply global and local measures of entropy to thecommuting networks of 25 US cities to capture structural diversity inresidential and work patterns. We identify significant relationships betweenthe heterogeneity of commuting origins and destinations with levels ofemployment and residential segregation, respectively. Finally, by comparing thelocal entropy values of low and high-income networks, we highlight howdisparities in entropy are indicative of both employment segregation andresidential inhomogeneities. Ultimately, this work motivates the application ofnetwork entropy to understand segregation not just from a residentialperspective, but an experiential one as well.

Network Entropy as a Measure of Socioeconomic Segregation in Residential and Employment Landscapes