  Social media play a key role in shaping citizens' political opinion.
According to the Eurobarometer, the percentage of EU citizens employing online
social networks on a daily basis has increased from 18% in 2010 to 48% in 2019.
The entwinement between social media and the unfolding of political dynamics
has motivated the interest of researchers for the analysis of users online
behavior - with particular emphasis on group polarization during debates and
echo-chambers formation. In this context, attention has been predominantly
directed towards the study of online relations between users while semantic
aspects have remained under-explored. In the present paper, we aim at filling
this gap by adopting a two-steps approach. First, we identify the discursive
communities animating the political debate in the run up of the 2018 Italian
Elections as groups of users with a significantly-similar retweeting behavior.
Second, we study the semantic mechanisms that shape their internal discussions
by monitoring, on a daily basis, the structural evolution of the semantic
networks they induce. Above and beyond specifying the semantic peculiarities of
the Italian electoral competition, our approach innovates studies of online
political discussions in two main ways. On the one hand, it grounds semantic
analysis within users' behaviors by implementing a method, rooted in
statistical theory, that guarantees that our inference of socio-semantic
structures is not biased by any unsupported assumption about missing
information; on the other, it is completely automated as it does not rest upon
any manual labelling (either based on the users' features or on their sharing
patterns). These elements make our method applicable to any Twitter discussion
regardless of the language or the topic addressed.
