  Echo chambers, i.e. clusters of users exposed to news and opinions in line
with their previous beliefs, were observed in many online debates on social
platforms. We propose a completely unbiased entropy-based method for detecting
echo chambers. The method is completely agnostic to the nature of the data. In
the Italian Twitter debate about the Covid-19 vaccination, we find a limited
presence of users in echo chambers (about 0.35% of all users). Nevertheless,
their impact on the formation of a common discourse is strong, as users in echo
chambers are responsible for nearly a third of the retweets in the original
dataset. Moreover, in the case study observed, echo chambers appear to be a
receptacle for disinformative content.
