About: A call for governments to pause Twitter censorship: a cross-sectional study using Twitter data as social-spatial sensors of COVID-19/SARS-CoV-2 research diffusion

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About: A call for governments to pause Twitter censorship: a cross-sectional study using Twitter data as social-spatial sensors of COVID-19/SARS-CoV-2 research diffusion Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	A call for governments to pause Twitter censorship: a cross-sectional study using Twitter data as social-spatial sensors of COVID-19/SARS-CoV-2 research diffusion
Creator	Patel, M Bornmann, Lutz Garas, George Frcs, Phd Patel, Vanash Phd, Robin Vanash, Mr
source	MedRxiv
abstract	Objectives: To determine whether Twitter data can be used as social-spatial sensors to show how research on COVID-19/SARS-CoV-2 diffuses through the population to reach the people that are especially affected by the disease. Design: Cross-sectional bibliometric analysis conducted between 23rd March and 14th April 2020. Setting: Three sources of data were used in the analysis: (1) deaths per number of population for COVID-19/SARS-CoV-2 retrieved from Coronavirus Resource Center at John Hopkins University and Worldometer, (2) publications related to COVID-19/SARS-CoV-2 retrieved from WHO COVID-19 database of global publications, and (3) tweets of these publications retrieved from Altmetric.com and Twitter. Main Outcome(s) and Measure(s): To map Twitter activity against number of publications and deaths per number of population worldwide and in the USA states. To determine the relationship between number of tweets as dependent variable and deaths per number of population and number of publications as independent variables. Results: Deaths per one hundred thousand population for countries ranged from 0 to 104, and deaths per one million population for USA states ranged from 2 to 513. Total number of publications used in the analysis was 1761, and total number of tweets used in the analysis was 751,068. Mapping of worldwide data illustrated that high Twitter activity was related to high numbers of COVID-19/SARS-CoV-2 deaths, with tweets inversely weighted with number of publications. Poisson regression models of worldwide data showed a positive correlation between the national deaths per number of population and tweets when holding the country's number of publications constant (coefficient 0.0285, S.E. 0.0003, p<0.001). Conversely, this relationship was negatively correlated in USA states (coefficient -0.0013, S.E. 0.0001, p<0.001). Conclusions: This study shows that Twitter can play a crucial role in the rapid research response during the COVID-19/SARS-CoV-2 global pandemic, especially to spread research with prompt public scrutiny. Governments are urged to pause censorship of social media platforms during these unprecedented times to support the scientific community's fight against COVID-19/SARS-CoV-2.
has issue date	2020-05-29(xsd:dateTime)
bibo:doi	10.1101/2020.05.27.20114983
has license	medrxiv
sha1sum (hex)	57c7d4b365a31f2f0696ebd3a60c6cf38e9110d9
schema:url	https://doi.org/10.1101/2020.05.27.20114983
resource representing a document's title	A call for governments to pause Twitter censorship: a cross-sectional study using Twitter data as social-spatial sensors of COVID-19/SARS-CoV-2 research diffusion
resource representing a document's body	covid:57c7d4b365a31f2f0696ebd3a60c6cf38e9110d9#body_text
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