  The daily exposure of social media users to propaganda and disinformation
campaigns has reinvigorated the need to investigate the local and global
patterns of diffusion of different (mis)information content on social media.
Echo chambers and influencers are often deemed responsible of both the
polarization of users in online social networks and the success of propaganda
and disinformation campaigns. This article adopts a data-driven approach to
investigate the structuration of communities and propaganda networks on Twitter
in order to assess the correctness of these imputations. In particular, the
work aims at characterizing networks of propaganda extracted from a Twitter
dataset by combining the information gained by three different classification
approaches, focused respectively on (i) using Tweets content to infer the
"polarization" of users around a specific topic, (ii) identifying users having
an active role in the diffusion of different propaganda and disinformation
items, and (iii) analyzing social ties to identify topological clusters and
users playing a "central" role in the network. The work identifies highly
partisan community structures along political alignments; furthermore,
centrality metrics proved to be very informative to detect the most active
users in the network and to distinguish users playing different roles; finally,
polarization and clustering structure of the retweet graphs provided useful
insights about relevant properties of users exposure, interactions, and
participation to different propaganda items.
