  Social structures influence a variety of human behaviors including mobility
patterns, but the extent to which one individual's movements can predict
another's remains an open question. Further, latent information about an
individual's mobility can be present in the mobility patterns of both social
and non-social ties, a distinction that has not yet been addressed. Here we
develop a "colocation" network to distinguish the mobility patterns of an ego's
social ties from those of non-social colocators, individuals not socially
connected to the ego but who nevertheless arrive at a location at the same time
as the ego. We apply entropy and predictability measures to analyse and bound
the predictive information of an individual's mobility pattern and the flow of
that information from their top social ties and from their non-social
colocators. While social ties generically provide more information than
non-social colocators, we find that significant information is present in the
aggregation of non-social colocators: 3-7 colocators can provide as much
predictive information as the top social tie, and colocators can replace up to
85% of the predictive information about an ego, compared with social ties that
can replace up to 94% of the ego's predictability. The presence of predictive
information among non-social colocators raises privacy concerns: given the
increasing availability of real-time mobility traces from smartphones,
individuals sharing data may be providing actionable information not just about
their own movements but the movements of others whose data are absent, both
known and unknown individuals.
