  We use multiple measures of graph complexity to evaluate the realism of
synthetically-generated networks of human activity, in comparison with several
stylized network models as well as a collection of empirical networks from the
literature. The synthetic networks are generated by integrating data about
human populations from several sources, including the Census, transportation
surveys, and geographical data. The resulting networks represent an
approximation of daily or weekly human interaction. Our results indicate that
the synthetically generated graphs according to our methodology are closer to
the real world graphs, as measured across multiple structural measures, than a
range of stylized graphs generated using common network models from the
literature.
