  Online social networking services (SNSs) involve communication activities
between large number of individuals over the public Internet and their crawled
records are often regarded as proxies of real (i.e., offline) interaction
structure. However, structure observed in these records might differ from real
counterparts because individuals may behave differently online and non-human
accounts may even participate. To understand the difference between online and
real social networks, we investigate an empirical communication network between
users on Twitter, which is perhaps one of the largest SNSs. We define a network
of user pairs that send reciprocal messages. Based on the mixing pattern
observed in this network, we argue that this network differs from conventional
understandings in the sense that there is a small number of distinctive users
that we call outsiders. Outsiders do not belong to any user groups but they are
connected with different groups, while not being well connected with each
other. We identify outsiders by maximizing the degree assortativity coefficient
of the network via node removal, thereby confirming that local structural
properties of outsiders identified are consistent with our hypothesis. Our
findings suggest that the existence of outsiders should be considered when
using Twitter communication networks for social network analysis.
