The supply and demand of news during COVID-19 and assessment of questionable sources production

Abstract

Social dialogue, the foundation of our democracies, is currently threatened by disinformation and partisanship, with their disrupting role on individual and collective awareness and detrimental effects on decisionmaking processes. Despite a great deal of attention to the news sphere itself, little is known about the subtle interplay between the offer and the demand for information. Still, a broader perspective on the news ecosystem, including both the producers and the consumers of information, is needed to build new tools to assess the health of the infosphere. Here, we combine in the same framework news supply, as mirrored by a fairly complete Italian news database -partially annotated for fake news, and news demand, as captured through the Google Trends data for Italy. Our investigation focuses on the temporal and semantic interplay of news, fake news, and searches in several domains, including the virus SARS-CoV-2 pandemic. Two main results emerge. First, disinformation is extremely reactive to people's interests and tends to thrive, especially when there is a mismatch between what people are interested in and what news outlets provide. Second, a suitably defined index can assess the level of disinformation only based on the available volumes of news and searches. Although our results mainly concern the Coronavirus subject, we provide hints that the same findings can have more general applications. We contend these results can be a powerful asset in informing campaigns against disinformation and providing news outlets and institutions with potentially relevant strategies.

Unveiling News Publishers Trustworthiness Through Social Interactions

“…Some recent work, such as that in [8,11,[29][30][31], has explored the social relationships between the social relationships between content producers and readers to reveal hidden information dynamics. A paper that has points in common with ours, though not intended to rank the degree of trustworthiness of a publisher, is that of Gravino et al [11]: the authors analyze the relationships between online news supply and online news demand. This study of the interplay is essential to reveal the mechanisms of information dynamics.…”

IRMA: the 335-million-word Italian coRpus for studying MisinformAtion

“…The second is based on the identification of particular textual content features, usually performed through natural language processing (NLP) tools, e.g., deep learning models. Because misinformation spreads alarmingly faster than reliable news (Vosoughi et al 2018;Gravino et al 2022), automatic tools allow to detect and limit the spread of false news quickly and without involving costly human effort. These tools are usually trained on large sets of textual data, which are for the most part in English language (see e.g., Zubiaga et al, 2016;Potthast et al, 2017;Castelo et al, 2019;Miani et al, 2022b).…”

Dynamics of information flow and engaging power of narratives in the polarised debate on vaccines

“…In this context, institutional and mainstream communication play a pivotal role [22]. The spread of false narratives among the public is indeed due not only, and not so much, to the presence of misinformation sources, but also to the inability of institutional and mainstream communication in addressing issues that are particularly sensitive and important [23], at least for a portion of the population.…”