  In the context of Twitter, social capitalists are specific users trying to
increase their number of followers and interactions by any means. These users
are not healthy for the Twitter network since they flaw notions of influence
and visibility. Indeed, it has recently been observed that they are real and
active users that can help malicious users such as spammers gaining influence.
Studying their behavior and understanding their position in Twitter is thus of
important interest. A recent work provided an efficient way to detect social
capitalists using two simple topological measures. Based on this detection
method, we study how social capitalists are distributed over Twitter's
friend-to-follower network. We are especially interested in analyzing how they
are organized, and how their links spread across the network. Answering these
questions allows to know whether the social capitalism methods increase the
actual visibility on the service. To that aim, we study the position of social
capitalists on Twitter w.r.t. the community structure of the network. We base
our work on the concept of community role of a node, which describes its
position in a network depending on its connectivity at the community level. The
topological measures originally defined to characterize these roles consider
only some aspects of community-related connectivity and rely on a set of
empirically fixed thresholds. We first show the limitations of such measures
and then extend and generalize them by considering new aspects of the
community-related connectivity. Moreover, we use an unsupervised approach to
distinguish the roles, in order to provide more flexibility relatively to the
studied system. We then apply our method to the case of social capitalists and
show that they are highly visible on Twitter, due to the specific roles they
occupy.
