First of all, to the so-called information overload problem (Melinat et al. 2016), almost without any form of traditional trusted intermediation (Eysenbach 2008 Carminati et al. In these platforms, people have the possibility to be connected and share both conversational and newsworthy content with friends and/or strangers into virtual communities (Zubiaga et al. Social media, in particular, have led to a drastic shift in the size and velocity at which information is communicated, and social media feeds are essential resources for accessing vast volumes of news and other types of informative contents in real time. In the present era, also known as information age (Floridi 2014), people are exposed to a significant amount of online content. The evaluations of the approach are carried out on a dataset of tweets related to COVID-19 collected between January and March 2020. Then, we assess and analyze the controversy and homogeneity among the different polarized groups obtained. To this aim, we propose an approach based on the application of a community detection strategy to distinct topology- and content-aware representations of the COVID-19 conversation graph. This article focuses on the study of the echo chamber phenomenon in the context of the COVID-19 pandemic, by considering both the relationships connecting individuals and semantic aspects related to the content they share over Twitter. echo chambers, people only "hear their own voice,” and divergent visions are no longer taken into account. However, due to the homophily property and selective exposure to information, social media have the tendency to create distinct groups of individuals whose ideas are highly polarized around certain topics. Social media allow to fulfill perceived social needs such as connecting with friends or other individuals with similar interests into virtual communities they have also become essential as news sources, microblogging platforms, in particular, in a variety of contexts including that of health.
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