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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.
J Med Internet Res. 2020 08 28; 22(8):e19629.JM

Abstract

BACKGROUND

The 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."

OBJECTIVE

This 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.

METHODS

Twitter'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.

RESULTS

Between 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).

CONCLUSIONS

The 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.

Authors+Show Affiliations

GECKO Institute for Medicine, Informatics & Economics, Heilbronn University, Heilbronn, Germany. Consumer Health Informatics SIG, German Association for Medical Informatics, Biometry & Epidemiology (GMDS e. V.), Cologne, Germany.Consumer Health Informatics SIG, German Association for Medical Informatics, Biometry & Epidemiology (GMDS e. V.), Cologne, Germany. Department of Medical Informatics, Heilbronn University, Heilbronn, Germany. Center for Machine Learning, Heilbronn University, Heilbronn, Germany.Consumer Health Informatics SIG, German Association for Medical Informatics, Biometry & Epidemiology (GMDS e. V.), Cologne, Germany. Department of Medical Informatics, Heilbronn University, Heilbronn, Germany.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32790641

Citation

Pobiruchin, Monika, et al. "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, vol. 22, no. 8, 2020, pp. e19629.
Pobiruchin M, Zowalla R, Wiesner M. 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. J Med Internet Res. 2020;22(8):e19629.
Pobiruchin, M., Zowalla, R., & Wiesner, M. (2020). 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, 22(8), e19629. https://doi.org/10.2196/19629
Pobiruchin M, Zowalla R, Wiesner M. 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. J Med Internet Res. 2020 08 28;22(8):e19629. PubMed PMID: 32790641.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - 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. AU - Pobiruchin,Monika, AU - Zowalla,Richard, AU - Wiesner,Martin, Y1 - 2020/08/28/ PY - 2020/04/25/received PY - 2020/08/11/accepted PY - 2020/06/23/revised PY - 2020/8/14/pubmed PY - 2020/9/10/medline PY - 2020/8/14/entrez KW - COVID-19 KW - SARS-CoV-2 KW - Twitter KW - disease surveillance KW - health informatics KW - infodemic KW - infodemiology KW - infoveillance KW - public health KW - social media SP - e19629 EP - e19629 JF - Journal of medical Internet research JO - J Med Internet Res VL - 22 IS - 8 N2 - BACKGROUND: The 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." OBJECTIVE: This 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. METHODS: Twitter'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. RESULTS: Between 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). CONCLUSIONS: The 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. SN - 1438-8871 UR - https://news.unboundmedicine.com/medline/citation/32790641/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_ L2 - https://www.jmir.org/2020/8/e19629/ DB - PRIME DP - Unbound Medicine ER -