  Twitter is one of the largest social networks using exclusively directed
links among accounts. This makes the Twitter social graph much closer to the
social graph supporting real life communications than, for instance, Facebook.
Therefore, understanding the structure of the Twitter social graph is
interesting not only for computer scientists, but also for researchers in other
fields, such as sociologists. However, little is known about how the
information propagation in Twitter is constrained by its inner structure. In
this paper, we present an in-depth study of the macroscopic structure of the
Twitter social graph unveiling the highways on which tweets propagate, the
specific user activity associated with each component of this macroscopic
structure, and the evolution of this macroscopic structure with time for the
past 6 years. For this study, we crawled Twitter to retrieve all accounts and
all social relationships (follow links) among accounts; the crawl completed in
July 2012 with 505 million accounts interconnected by 23 billion links. Then,
we present a methodology to unveil the macroscopic structure of the Twitter
social graph. This macroscopic structure consists of 8 components defined by
their connectivity characteristics. Each component group users with a specific
usage of Twitter. For instance, we identified components gathering together
spammers, or celebrities. Finally, we present a method to approximate the
macroscopic structure of the Twitter social graph in the past, validate this
method using old datasets, and discuss the evolution of the macroscopic
structure of the Twitter social graph during the past 6 years.
