ABSTRACT
This paper compares the coverage of the H1N1 and Covid-19 pandemics in ten prominent US daily newspapers. We selected articles that reference disease-specific keywords, published in the period between the declaration of a Public Health Emergency of International Concern by the World Health Organization and the first peak in laboratory-confirmed cases in the USA (20550 articles on Covid-19 and 1705 articles on H1N1). We analyzed the dataset via topic models and semantic networks, which, in a semiotic approach, are understood as iconic models. As the Covid-19 virus produced the first global pandemic in the age of social media, this comparative analysis illustrates how the news media changed the mediasphere in general. During the H1N1 pandemic (2009-2010), newly emerging social media were not mainstream, having a limited impact compared to 2020 at the outbreak of Covid-19. By 2020, social media have definingly changed the mediasphere. Given their affordance for the virulent transmission of media products, the rise of social media stirred the relativization of knowledge and mistrust towards traditional authority and legacy media. Paradoxically, this both democratizes public debate and opens opportunities for misinformation. In this context, the Covid-19 pandemic has been accompanied by a global infodemic, with adverse impact on global health. While the two pandemics are very different, comparing media representations in their early stages, when the viral spread was unpredictable, offers an insight into how the emergence of social media impacted traditional newspapers’ approach to events of global concern. The analysis reveals that ideological commitments are expressed through the same correlation of topics in both corpora but that, overall, the discourses have different structures. We argue that the remarkable stability of ideological discourses displays what McLuhan termed Narcissus narcosis, namely the numbness experienced socially during media changes. © 2021 Alin Olteanu, Florian Rabitz and Augustė Nalivaikė.
ABSTRACT
The year 2020 will remain in the memory of all mankind as the year of the COVID-19 pandemic. The pandemic has affected the world economy, caused more than a million deaths in 2020 alone, changed the way people work and learn and, last but not least, changed the way people interact in society. Social distancing, along with wearing a face mask, is the best solution to prevent the spread of COVID-19 virus. What happens when in certain spaces social distance is difficult and can be accidentally violated without intention? In the absence of widely available tests, not only for people but also for surfaces or indoor air, the risk of contamination is very difficult to assess. This paper proposes a simple method, with low cost and widely implementable, to warn of respecting the density of people in a room. It proposes a dual monitoring system based on Internet of Things (IoT) to assess the indoor air quality and risk of COVID-19 transmission. © 2021 IEEE.