  This study evaluates the effectiveness of using Google Maps Location History
data to identify joint activities in social networks. To do so, an experiment
was conducted where participants were asked to execute daily schedules designed
to simulate daily travel incorporating joint activities. For Android devices,
detection rates for 4-person group activities ranged from 22% under the
strictest spatiotemporal accuracy criteria to 60% under less strict yet still
operational criteria. The performance of iPhones was markedly worse than
Android devices, irrespective of accuracy criteria. In addition, logit models
were estimated to evaluate factors affecting activity detection given different
spatiotemporal accuracy thresholds. In terms of effect magnitudes, non-trivial
effects on joint activity detection probability were found for floor area ratio
(FAR) at location, activity duration, Android device ratio, device model ratio,
whether the destination was an open space or not, and group size.
  Although current activity detection rates are not ideal, these levels must be
weighed against the potential of observing travel behavior over long periods of
time, and that Google Maps Location History data could potentially be used in
conjunction with other data-gathering methodologies to compensate for some of
its limitations.
