  Studies using massive, passively data collected from communication
technologies have revealed many ubiquitous aspects of social networks, helping
us understand and model social media, information diffusion, and organizational
dynamics. More recently, these data have come tagged with geographic
information, enabling studies of human mobility patterns and the science of
cities. We combine these two pursuits and uncover reproducible mobility
patterns amongst social contacts. First, we introduce measures of mobility
similarity and predictability and measure them for populations of users in
three large urban areas. We find individuals' visitations patterns are far more
similar to and predictable by social contacts than strangers and that these
measures are positively correlated with tie strength. Unsupervised clustering
of hourly variations in mobility similarity identifies three categories of
social ties and suggests geography is an important feature to contextualize
social relationships. We find that the composition of a user's ego network in
terms of the type of contacts they keep is correlated with mobility behavior.
Finally, we extend a popular mobility model to include movement choices based
on social contacts and compare it's ability to reproduce empirical measurements
with two additional models of mobility.
