  In the analysis of Twitter debate, the recent literature focused on
discursive communities, i.e. clusters of accounts interacting among themselves
via retweets. In the present work, we studied discursive communities in 8
different thematic Twitter datasets in various languages. Surprisingly, we
observed that almost all discursive communities therein display a bow-tie
structure during political or societal debates. Instead, they are absent when
the argument of the discussion is different as sport events, as in the case of
Euro2020 Turkish and Italian datasets. We furthermore analysed the quality of
the content created in the various sectors of the different discursive
communities, using the domain annotation from the fact-checking website
Newsguard: we observe that, when the discursive community is affected by
m/disinformation, the content with the lowest quality is the ones produced and
shared in SCC and, in particular, a strong incidence of low- or non-reputable
messages is present in the flow of retweets between the SCC and the OUT
sectors. In this sense, in discursive communities affected by m/disinformation,
the greatest part of the accounts has access to a great variety of contents,
but whose quality is, in general, quite low; such a situation perfectly
describes the phenomenon of infodemic, i.e. the access to "an excessive amount
of information about a problem, which makes it difficult to identify a
solution", according to WHO).

Social and Information Networks;Data Analysis, Statistics and Probability