  The Covid-19 pandemic has had a deep impact on the lives of the entire world
population, inducing a participated societal debate. As in other contexts, the
debate has been the subject of several d/misinformation campaigns; in a quite
unprecedented fashion, however, the presence of false information has seriously
put at risk the public health. In this sense, detecting the presence of
malicious narratives and identifying the kinds of users that are more prone to
spread them represent the first step to limit the persistence of the former
ones. In the present paper we analyse the semantic network observed on Twitter
during the first Italian lockdown (induced by the hashtags contained in
approximately 1.5 millions tweets published between the 23rd of March 2020 and
the 23rd of April 2020) and study the extent to which various discursive
communities are exposed to d/misinformation arguments. As observed in other
studies, the recovered discursive communities largely overlap with traditional
political parties, even if the debated topics concern different facets of the
management of the pandemic. Although the themes directly related to
d/misinformation are a minority of those discussed within our semantic
networks, their popularity is unevenly distributed among the various discursive
communities.
