  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.
