The link between reported cases of COVID-19 and the Infodemic Risk Index: A worldwide perspective.

In this brief report we followed the evolution of the COVID-19 Infodemic Risk Index during 2020 and clarified its connection with the epidemic waves, focusing specifically on their co-evolution in Europe, South America, and South-eastern Asia. Using 640 million tweets collected by the Infodemic Observatory and the open access dataset published by Our World in Data regarding COVID-19 worldwide reported cases, we analyze the COVID-19 infodemic vs. pandemic co-evolution from January 2020 to December 2020. We find that a characteristic pattern emerges at the global scale: a decrease in misinformation on Twitter as the number of COVID-19 confirmed cases increases. Similar local variations highlight how this pattern could be influenced both by the strong content moderation policy enforced by Twitter after the first pandemic wave and by the phenomenon of selective exposure that drives users to pick the most visible and reliable news sources available.

The "Green Pass" Controversy in the Italian Twittersphere: a Digital Methods Mapping

In this paper we developed a digital methods mapping of the controversy arises from the adoption of the so-called "Green Pass" in Italy Adopting an "agnostic" approach to our object of study, we used a well-established research design: namely, to collect all the tweets that contain words related to conversations about the green pass in Italy (e.g.: green pass, #greenpass). In this way, the sample collected amounts to 4.307.487 tweets, published between June 15, 2021, and December 15, 2021. To bring out the "voices" of the different actors involved in the controversy we adopted a quali-quantitative approach: on the one hand, by means of computational techniques, we reconstructed the structural relations in which the actors are involved and its evolution over time;on the other hand, by means of content analysis we enriched our map with an interpretation of the discourse surrounding the controversy. Finally, these cartographic results are discussed considering the Italian media system functioning, in order to understand how its conformation may have influenced the public debate concerning the green pass.

The link between reported cases of COVID-19 and the Infodemic Risk Index: A worldwide perspective

In this brief report we followed the evolution of the COVID-19 Infodemic Risk Index during 2020 and clarified its connection with the epidemic waves, focusing specifically on their co-evolution in Europe, South America, and South-eastern Asia. Using 640 million tweets collected by the Infodemic Observatory and the open access dataset published by Our World in Data regarding COVID-19 worldwide reported cases, we analyze the COVID-19 infodemic vs. pandemic co-evolution from January 2020 to December 2020. We find that a characteristic pattern emerges at the global scale: a decrease in misinformation on Twitter as the number of COVID-19 confirmed cases increases. Similar local variations highlight how this pattern could be influenced both by the strong content moderation policy enforced by Twitter after the first pandemic wave and by the phenomenon of selective exposure that drives users to pick the most visible and reliable news sources available.

Emergence of knowledge communities and information centralization during the COVID-19 pandemic.

BACKGROUND: As COVID-19 spreads worldwide, an infodemic - i.e., an over-abundance of information, reliable or not - spreads across the physical and the digital worlds, triggering behavioral responses which cause public health concern. METHODS: We study 200 million interactions captured from Twitter during the early stage of the pandemic, from January to April 2020, to understand its socio-informational structure on a global scale. FINDINGS: The COVID-19 global communication network is characterized by knowledge groups, hierarchically organized in sub-groups with well-defined geo-political and ideological characteristics. Communication is mostly segregated within groups and driven by a small number of subjects: 0.1% of users account for up to 45% and 10% of activities and news shared, respectively, centralizing the information flow. INTERPRETATION: Contradicting the idea that digital social media favor active participation and co-creation of online content, our results imply that public health policy strategies to counter the effects of the infodemic must not only focus on information content, but also on the social articulation of its diffusion mechanisms, as a given community tends to be relatively impermeable to news generated by non-aligned sources.