Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study

BackgroundThe spread of the 2019 novel coronavirus disease, COVID-19, across Asia and Europe sparked a significant increase in public interest and media coverage, including on social media platforms such as Twitter. In this context, the origin of information plays a central r...

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Main Authors: Pobiruchin, Monika, Zowalla, Richard, Wiesner, Martin
Format: Article
Language:English
Published: JMIR Publications 2020-08-01
Series:Journal of Medical Internet Research
Online Access:http://www.jmir.org/2020/8/e19629/
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spelling doaj-bae36ab631e34fe1a3d522b6b8826b742021-04-02T18:56:34ZengJMIR PublicationsJournal of Medical Internet Research1438-88712020-08-01228e1962910.2196/19629Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance StudyPobiruchin, MonikaZowalla, RichardWiesner, Martin BackgroundThe spread of the 2019 novel coronavirus disease, COVID-19, across Asia and Europe sparked a significant increase in public interest and media coverage, including on social media platforms such as Twitter. In this context, the origin of information plays a central role in the dissemination of evidence-based information about the SARS-CoV-2 virus and COVID-19. On February 2, 2020, the World Health Organization (WHO) constituted a “massive infodemic” and argued that this situation “makes it hard for people to find trustworthy sources and reliable guidance when they need it.” ObjectiveThis infoveillance study, conducted during the early phase of the COVID-19 pandemic, focuses on the social media platform Twitter. It allows monitoring of the dynamic pandemic situation on a global scale for different aspects and topics, languages, as well as regions and even whole countries. Of particular interest are temporal and geographical variations of COVID-19–related tweets, the situation in Europe, and the categories and origin of shared external resources. MethodsTwitter’s Streaming application programming interface was used to filter tweets based on 16 prevalent hashtags related to the COVID-19 outbreak. Each tweet’s text and corresponding metadata as well as the user’s profile information were extracted and stored into a database. Metadata included links to external resources. A link categorization scheme—introduced in a study by Chew and Eysenbach in 2009—was applied onto the top 250 shared resources to analyze the relative proportion for each category. Moreover, temporal variations of global tweet volumes were analyzed and a specific analysis was conducted for the European region. ResultsBetween February 9 and April 11, 2020, a total of 21,755,802 distinct tweets were collected, posted by 4,809,842 distinct Twitter accounts. The volume of #covid19-related tweets increased after the WHO announced the name of the new disease on February 11, 2020, and stabilized at the end of March at a high level. For the regional analysis, a higher tweet volume was observed in the vicinity of major European capitals or in densely populated areas. The most frequently shared resources originated from various social media platforms (ranks 1-7). The most prevalent category in the top 50 was “Mainstream or Local News.” For the category “Government or Public Health,” only two information sources were found in the top 50: US Centers for Disease Control and Prevention at rank 25 and the WHO at rank 27. The first occurrence of a prevalent scientific source was Nature (rank 116). ConclusionsThe naming of the disease by the WHO was a major signal to address the public audience with public health response via social media platforms such as Twitter. Future studies should focus on the origin and trustworthiness of shared resources, as monitoring the spread of fake news during a pandemic situation is of particular importance. In addition, it would be beneficial to analyze and uncover bot networks spreading COVID-19–related misinformation.http://www.jmir.org/2020/8/e19629/
collection DOAJ
language English
format Article
sources DOAJ
author Pobiruchin, Monika
Zowalla, Richard
Wiesner, Martin
spellingShingle Pobiruchin, Monika
Zowalla, Richard
Wiesner, Martin
Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study
Journal of Medical Internet Research
author_facet Pobiruchin, Monika
Zowalla, Richard
Wiesner, Martin
author_sort Pobiruchin, Monika
title Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study
title_short Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study
title_full Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study
title_fullStr Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study
title_full_unstemmed Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study
title_sort temporal and location variations, and link categories for the dissemination of covid-19–related information on twitter during the sars-cov-2 outbreak in europe: infoveillance study
publisher JMIR Publications
series Journal of Medical Internet Research
issn 1438-8871
publishDate 2020-08-01
description BackgroundThe spread of the 2019 novel coronavirus disease, COVID-19, across Asia and Europe sparked a significant increase in public interest and media coverage, including on social media platforms such as Twitter. In this context, the origin of information plays a central role in the dissemination of evidence-based information about the SARS-CoV-2 virus and COVID-19. On February 2, 2020, the World Health Organization (WHO) constituted a “massive infodemic” and argued that this situation “makes it hard for people to find trustworthy sources and reliable guidance when they need it.” ObjectiveThis infoveillance study, conducted during the early phase of the COVID-19 pandemic, focuses on the social media platform Twitter. It allows monitoring of the dynamic pandemic situation on a global scale for different aspects and topics, languages, as well as regions and even whole countries. Of particular interest are temporal and geographical variations of COVID-19–related tweets, the situation in Europe, and the categories and origin of shared external resources. MethodsTwitter’s Streaming application programming interface was used to filter tweets based on 16 prevalent hashtags related to the COVID-19 outbreak. Each tweet’s text and corresponding metadata as well as the user’s profile information were extracted and stored into a database. Metadata included links to external resources. A link categorization scheme—introduced in a study by Chew and Eysenbach in 2009—was applied onto the top 250 shared resources to analyze the relative proportion for each category. Moreover, temporal variations of global tweet volumes were analyzed and a specific analysis was conducted for the European region. ResultsBetween February 9 and April 11, 2020, a total of 21,755,802 distinct tweets were collected, posted by 4,809,842 distinct Twitter accounts. The volume of #covid19-related tweets increased after the WHO announced the name of the new disease on February 11, 2020, and stabilized at the end of March at a high level. For the regional analysis, a higher tweet volume was observed in the vicinity of major European capitals or in densely populated areas. The most frequently shared resources originated from various social media platforms (ranks 1-7). The most prevalent category in the top 50 was “Mainstream or Local News.” For the category “Government or Public Health,” only two information sources were found in the top 50: US Centers for Disease Control and Prevention at rank 25 and the WHO at rank 27. The first occurrence of a prevalent scientific source was Nature (rank 116). ConclusionsThe naming of the disease by the WHO was a major signal to address the public audience with public health response via social media platforms such as Twitter. Future studies should focus on the origin and trustworthiness of shared resources, as monitoring the spread of fake news during a pandemic situation is of particular importance. In addition, it would be beneficial to analyze and uncover bot networks spreading COVID-19–related misinformation.
url http://www.jmir.org/2020/8/e19629/
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