Understanding segregation is essential to develop planning tools for building more inclusive cities. Theoretically, segregation at the work place has been described as lower compared to residential segregation given the importance of skill complementarity among other productive factors shaping the economies of cities. This paper tackles segregation during working hours from a dynamical perspective by focusing on the movement of urbanites across the city. In contrast to measuring residential patterns of segregation, we used mobile phone data to infer home-work trajectory net- works and apply a community detection algorithm to the example city of Santiago, Chile. We then describe qualitatively and quantitatively outlined communities, in terms of their socio eco- nomic composition. We then evaluate segregation for each of these communities as the probability that a person from a specific community will interact with a co-worker from the same commu- nity. Finally, we compare these results with simulations where a new work location is set for each real user, following the empirical probability distributions of home-work distances and angles of direction for each community. Methodologically, this study shows that segregation during working hours for Santiago is unexpectedly high for most of the city with the exception of its central and business district. In fact, the only community that is not statistically segregated corresponds to the downtown area of Santiago, described as a zone of encounter and integration across the city.
from cs updates on arXiv.org http://ift.tt/2ntg5kb
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