Gozzi, Nicolo, Tizzani, Michele, Starnini, Michele, Ciulla, Fabio, Paolotti, Daniela, Panisson, Andre and Perra, Nicola ORCID: 0000-0002-5559-3064 (2020) Collective response to the media coverage of COVID-19 pandemic on Reddit and Wikipedia: mixed-methods analysis. Journal of Medical Internet Research, 22 (10):e21597. ISSN 1439-4456 (Print), 1438-8871 (Online) (doi:https://doi.org/10.2196/21597)

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Abstract

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

Objective: The goal of this work is to provide a characterization of media coverage and online collective response to COVID-19 pandemic in four countries: Italy, United Kingdom, United States, and Canada.

Methods: We collect a heterogeneous dataset including 227’768 online news articles and 13’448 YouTube videos published by mainstream media, 107’898 users posts and 3’829’309 comments on the social media platform Reddit, and 278’456’892 views to COVID-19 related Wikipedia pages.

Results: Our results show that public attention, quantified as users activity on Reddit and active searches on Wikipedia pages, is mainly driven by media coverage and declines rapidly, while news exposure and COVID-19 incidence remain high. Furthermore, by using an unsupervised, dynamical topic modeling approach, we show that while the attention dedicated to different topics by media and online 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 collective awareness, risk perception and thus on tendencies towards behavioural changes

Item Type:	Article
Uncontrolled Keywords:	social media, news coverage, digital epidemiology, data science, topic modeling, pandemic, covid19
Subjects:	H Social Sciences > HM Sociology
Faculty / School / Research Centre / Research Group:	Faculty of Business Faculty of Business > Department of International Business & Economics Faculty of Business > Networks and Urban Systems Centre (NUSC) Faculty of Business > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA)
Last Modified:	01 Dec 2020 15:36
URI:	http://gala.gre.ac.uk/id/eprint/29630

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