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Tytuł:
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A Social Network Analysis of Tweets Related to Masks during the COVID-19 Pandemic.
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Autorzy:
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Ahmed W; Newcastle University Business School, Newcastle University, Newcastle upon Tyne NE1 4SE, UK.
Vidal-Alaball J; Health Promotion in Rural Areas Research Group, Gerència Territorial de la Catalunya Central, Institut Català de la Salut, 08272 Sant Fruitós de Bages, Spain.; Unitat de Suport a la Recerca de la Catalunya Central, Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, 08272 Sant Fruitós de Bages, Spain.
Lopez Segui F; TIC Salut Social, Generalitat de Catalunya, 08005 Barcelona, Spain.; Center for Research in Health and Economics (CRES-UPF), Universitat Pompeu Fabra, 08002 Barcelona, Spain.
Moreno-Sánchez PA; School of Health Care and Social Work, Seinäjoki University of Applied Sciences, 60100 Seinäjoki, Finland.
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Źródło:
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International journal of environmental research and public health [Int J Environ Res Public Health] 2020 Nov 07; Vol. 17 (21). Date of Electronic Publication: 2020 Nov 07.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: Basel : MDPI, c2004-
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MeSH Terms:
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Coronavirus Infections*/prevention & control
Masks*
Pandemics*/prevention & control
Pneumonia, Viral*/prevention & control
Social Media*
Betacoronavirus ; COVID-19 ; Humans ; Public Health ; SARS-CoV-2 ; Social Networking
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References:
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Contributed Indexing:
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Keywords: COVID-19; coronavirus; masks; public health; transmission; twitter
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Entry Date(s):
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Date Created: 20201111 Date Completed: 20201113 Latest Revision: 20201218
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Update Code:
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20240105
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PubMed Central ID:
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PMC7664625
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DOI:
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10.3390/ijerph17218235
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PMID:
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33171843
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Background: High compliance in wearing a mask is a crucial factor for stopping the transmission of COVID-19. Since the beginning of the pandemic, social media has been a key communication channel for citizens. This study focused on analyzing content from Twitter related to masks during the COVID-19 pandemic.
Methods: Twitter data were collected using the keyword "mask" from 27 June 2020 to 4 July 2020. The total number of tweets gathered were n = 452,430. A systematic random sample of 1% ( n = 4525) of tweets was analyzed using social network analysis. NodeXL (Social Media Research Foundation, California, CA, USA) was used to identify users ranked influential by betweenness centrality and was used to identify key hashtags and content.
Results: The overall shape of the network resembled a community network because there was a range of users conversing amongst each other in different clusters. It was found that a range of accounts were influential and/or mentioned within the network. These ranged from ordinary citizens, politicians, and popular culture figures. The most common theme and popular hashtags to emerge from the data encouraged the public to wear masks.
Conclusion: Towards the end of June 2020, Twitter was utilized by the public to encourage others to wear masks and discussions around masks included a wide range of users.