Conference Program

The Covid-19 pandemic represented a moment of profound transformation in the processes of science communication. The centrality of data in the public narrative of the health crisis (especially, during the initial period from March to May 2020 and during the first phase of vaccine distribution in January 2021) made journalism a key mediator between scientific knowledge institutions and the public. Tables, graphs, percentages, and statistical indicators, along with medical and scientific terminology, became a constant presence in everyday news coverage, turning data-driven journalism into one of the main channels through which scientific information reached a mass audience.

This contribution reflects on the role of data in science communication through the results of an empirical study on how Italian audiences perceived and interpreted data-driven news during the pandemic. The research is part of the broader project The Social Effects of Fake News and focuses on how audiences approach informational content that incorporates scientific and statistical data. The study is based on a survey conducted between 2020 and 2021 with 399 respondents across Italy, investigating the relationship between media consumption, trust in institutions and the ability to interpret news items involving scientific data.

The pandemic clearly showed that science communication does not only concern the dissemination of scientific results, but also the translation of technical languages and complex data systems into narratives that are understandable and socially meaningful. In this context, journalism assumed a crucial epistemic role: not only reporting information, but interpreting and contextualizing data produced by the scientific community. However, the increasing visibility of scientific data in news coverage also revealed new tensions in the relationship between science, media, and public opinion, particularly within an environment characterized by information disorder and the so-called “infodemic.”

The findings of the research highlight a paradox in the relationship between audiences and science-related information. A significant portion of respondents expressed high levels of trust in doctors and scientists; at the same time, the same respondents showed a relatively high propensity to trust epidemiological or statistical data conveyed and used by the same doctors and scientists.

To explain this contradiction, the research proposes the model of the "know-it-all approach". This model describes an attitude in which individuals believe they possess greater interpretative competence than others when evaluating events, policies, and data. Within this framework, scientific data are not rejected outright; rather, they are reinterpreted through personal experience, prior beliefs, or alternative narratives. The result is a tension between scientific authority, journalistic mediation and the social perception of scientific evidence.

These findings suggest that, in contemporary media environments characterized by hybridization and platformization, science communication cannot rely solely on the presentation of data or scientific evidence. Instead, it requires greater attention to the ways in which data are translated, contextualized and narratively framed. Data-driven journalism represent therefore a crucial space for science communication, provided it develops narrative and transmedia strategies capable of making data understandable, verifiable, and socially meaningful for diverse audiences.