  We study the social structure of Facebook "friendship" networks at one
hundred American colleges and universities at a single point in time, and we
examine the roles of user attributes - gender, class year, major, high school,
and residence - at these institutions. We investigate the influence of common
attributes at the dyad level in terms of assortativity coefficients and
regression models. We then examine larger-scale groupings by detecting
communities algorithmically and comparing them to network partitions based on
the user characteristics. We thereby compare the relative importances of
different characteristics at different institutions, finding for example that
common high school is more important to the social organization of large
institutions and that the importance of common major varies significantly
between institutions. Our calculations illustrate how microscopic and
macroscopic perspectives give complementary insights on the social organization
at universities and suggest future studies to investigate such phenomena
further.
