Evidence map›Paper›PMID 32960775›Full record

ArticleJournal of medical Internet research2020

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

Nicolò Gozzi, Michele Tizzani, Michele Starnini, Fabio Ciulla, Daniela Paolotti, André Panisson, Nicola Perra

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

57 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Nicolò GozziUniversity of Greenwich, London, United Kingdom.ORCID 0000-0002-9996-3194
Michele TizzaniISI Foundation, Torino, Italy.ORCID 0000-0003-3068-5111
Michele StarniniISI Foundation, Torino, Italy.ORCID 0000-0002-9161-5339
Fabio CiullaQuid Inc, San Francisco, CA, United States.ORCID 0000-0002-2637-1737
Daniela PaolottiISI Foundation, Torino, Italy.ORCID 0000-0003-1356-3470
André PanissonISI Foundation, Torino, Italy.ORCID 0000-0002-3336-0374
Nicola PerraUniversity of Greenwich, London, United Kingdom.ORCID 0000-0002-5559-3064

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

objectiveThe 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.

methodsWe 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.

resultsOur 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.

conclusionsOverall, 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.

Indexed as

CommunicationAdolescentAdultBetacoronavirusCanadaCoronavirus InfectionsCOVID-19Disease OutbreaksFemaleGlobal HealthHumansItalyMaleMiddle AgedPandemicsPneumonia, ViralbehaviorCOVID-19data sciencedigital epidemiologyinfodemicinfodemiologyinformationinfoveillancenews coveragepandemicRedditresponserisk perceptionsocial mediatopic modelingWikipedia

Identifiers

PMID32960775
PMCPMC7553788

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.