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. 2020 Oct 12;22(10):e21597.
doi: 10.2196/21597.

Collective Response to Media Coverage of the COVID-19 Pandemic on Reddit and Wikipedia: Mixed-Methods Analysis

Nicolò Gozzi  1 , Michele Tizzani  2 , Michele Starnini  2 , Fabio Ciulla  3 , Daniela Paolotti  2 , André Panisson  2 , Nicola Perra  1
Affiliations

Collective Response to Media Coverage of the COVID-19 Pandemic on Reddit and Wikipedia: Mixed-Methods Analysis

Nicolò Gozzi et al. J Med Internet Res. .

Abstract

Background: The exposure and consumption of information during epidemic outbreaks may alter people's risk perception and trigger behavioral changes, which can ultimately affect the evolution of the disease. It is thus of utmost importance to map the dissemination of information by mainstream media outlets and the public response to this information. However, our understanding of this exposure-response dynamic during the COVID-19 pandemic is still limited.

Objective: The goal of this study is to characterize the media coverage and collective internet response to the COVID-19 pandemic in four countries: Italy, the United Kingdom, the United States, and Canada.

Methods: We collected a heterogeneous data set including 227,768 web-based news articles and 13,448 YouTube videos published by mainstream media outlets, 107,898 user posts and 3,829,309 comments on the social media platform Reddit, and 278,456,892 views of COVID-19-related Wikipedia pages. To analyze the relationship between media coverage, epidemic progression, and users' collective web-based response, we considered a linear regression model that predicts the public response for each country given the amount of news exposure. We also applied topic modelling to the data set using nonnegative matrix factorization.

Results: Our results show that public attention, quantified as user activity on Reddit and active searches on Wikipedia pages, is mainly driven by media coverage; meanwhile, this activity declines rapidly while news exposure and COVID-19 incidence remain high. Furthermore, using an unsupervised, dynamic topic modeling approach, we show that while the levels of attention dedicated to different topics by media outlets and internet users are in good accordance, interesting deviations emerge in their temporal patterns.

Conclusions: Overall, our findings offer an additional key to interpret public perception and response to the current global health emergency and raise questions about the effects of attention saturation on people's collective awareness and risk perception and thus on their tendencies toward behavioral change.

Keywords: COVID-19; Reddit; Wikipedia; behavior; data science; digital epidemiology; infodemic; infodemiology; information; infoveillance; news coverage; pandemic; response; risk perception; social media; topic modeling.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Normalized weekly volumes of news articles and YouTube videos, Reddit comments, and Wikipedia page views related to the COVID-19 pandemic and the incidence of COVID-19 in different countries.
Figure 2
Figure 2
Shares of citations of China versus home country locations by Italian, UK, US, and Canadian news outlets before and after the first COVID-19 death occurred in each country.
Figure 3
Figure 3
Differences in interest percentage shares of different topics by traditional media outlets and Reddit users. For example, +2% on the x-axis indicates that traditional media dedicates proportionally 2% more attention to that specific topic than Reddit users. CDC: US Centers for Disease Control and Prevention; UK: United Kingdom; WHO: World Health Organization.
Figure 4
Figure 4
Scatter plot with the 64 topics extracted via nonnegative matrix factorization. The x-axis and y-axis coordinates indicate when a topic achieved 50% of its relevance in news outlets and on Reddit, respectively, during our analysis interval. CDC: US Centers for Disease Control and Prevention.
See this image and copyright information in PMC

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