  Understanding social dynamics that govern human phenomena, such as
communications and social relationships is a major problem in current
computational social sciences. In particular, given the unprecedented success
of online social networks (OSNs), in this paper we are concerned with the
analysis of aggregation patterns and social dynamics occurring among users of
the largest OSN as the date: Facebook. In detail, we discuss the mesoscopic
features of the community structure of this network, considering the
perspective of the communities, which has not yet been studied on such a large
scale. To this purpose, we acquired a sample of this network containing
millions of users and their social relationships; then, we unveiled the
communities representing the aggregation units among which users gather and
interact; finally, we analyzed the statistical features of such a network of
communities, discovering and characterizing some specific organization patterns
followed by individuals interacting in online social networks, that emerge
considering different sampling techniques and clustering methodologies. This
study provides some clues of the tendency of individuals to establish social
interactions in online social networks that eventually contribute to building a
well-connected social structure, and opens space for further social studies.
