The COVID-19 infodemic on Twitter: dialogic contraction within the echo chambers

Fake news and misinformation are a key topic when discussing social media analysis research. Special attention has been paid to how social media discourse, rather than focusing on the correct identification of sources and voices, can end up constructing trust and credibility by emphasising shared identities and positions, usually in opposition to other views. Studies on “echo chambers” look at how the views of others are systematically rejected and used instrumentally to support one’s own beliefs. Twitter discourse is often a case in point. The focus of our analysis is on the language that manifests the writer’s position, starting from the concept of engagement as defined in Martin and White’s (2005) appraisal framework. This indicates the speaker’s degree of commitment to what is being expressed and manifests the speaker’s attitudes to opening and closing the dialogic space for external views. Using a corpus of tweets and one of journalistic texts on the pandemic, we test the hypothesis that the space given to dialogic contraction on Twitter may be wider than that provided by traditional journalism. The study - based on frequency analysis, concordance analysis, and word embedding - centres on a predefined list of appraisal markers indicating contraction or expansion. We look at the relative frequency of these markers and at their role in the ongoing debate. The results show that there are specific markers that dominate Twitter discourse: adversative “but”, negative “no”/“not”, and cognitive verbs like “know” and “think”. A closer analysis of concordances of negatives and cognitive verbs shows that it is possible to identify patterns that are clear signals of explicit denials, whether in representing a position or rejecting it, and that the verbs are used as markers of ideological positioning. Twitter thus turns out to be characterised by positioning that emphasises contrasting views and denial of other positions.