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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Feb 7, 2023
Date Accepted: May 30, 2023

The final, peer-reviewed published version of this preprint can be found here:

Global COVID-19 Policy Engagement With Scientific Research Information: Altmetric Data Study

PARK HW, YOON HY

Global COVID-19 Policy Engagement With Scientific Research Information: Altmetric Data Study

J Med Internet Res 2023;25:e46328

DOI: 10.2196/46328

PMID: 37384384

PMCID: 10365591

Global COVID-19 Policy Engagement with Scientific Research Information: Altmetric Data Approach

  • HAN WOO PARK; 
  • HO YOUNG YOON

ABSTRACT

Background:

Previous investigations about COVID-19 scholarly articles have typically concentrated on the bibliometric characteristics of COVID-19 research articles. However, there is a dearth of research that identifies the institutional actors and their locations that cite the most recent scientific contributions related to topics covered by COVID-19 in the policy domain.

Objective:

The purpose of this research is to look at online citation network and knowledge structure of COVID-19 research across policy domains over the two years from Jan 2020 to Jan 2022, particularly focusing on geographical-related frequency. Two research questions are asked. The first question is to ask that who has been the most active in terms of policy engagement with science and research information sharing during the COVID-19 pandemic, particularly by countries and organization type. The second question is to ask whether there are any significant difference in the types of coronavirus research shared in each country and continental distribution.

Methods:

The Altmetric database is utilized to collect policy report citations of scientific articles for three topic terms (COVID-19, COVID-19 vaccine, and COVID-19 variant). The URLs of policy agencies that cited COVID-19 research are provided by Altmetric. The scientific articles used for citations are extracted from journals indexed by PubMed. COVID-19, COVID-19 vaccine, and COVID-19 variant research outputs between January 1, 2020 and January 31, 2020 were 216,787, 16,748 and 2,777, respectively. The study examines the frequency of citations based on policy institutional domains such as inter-governmental organization, national or domestic governmental organization, and non-governmental organization.

Results:

WHO is the most notable institution to cite three COVID-19-related research outputs. WHO has actively sought and disseminated information regarding the COVID-19 pandemic. The COVID-19 vaccine citation network had the most extensive connections in terms of degree centrality, 2-local centrality, and eigenvector centrality with three key terms. The Netherlands, the United States, the United Kingdom, and Australia were the nations that sought and shared the most information on the COVID-19 vaccine. These nations had witnessed a rapid increase in COVID-19-infected cases. Although developing nations can obtain COVID-19 vaccine information more quickly and easily than the past, their marginal position in the global network indicated that they were isolated from enriched COVID-19 pandemic content

Conclusions:

The global scientific network ecology in the COVID-19 pandemic shows distinctive kinds of links that are concentrated around the World Health Organization (WHO). According to an analysis of the various types of citation ties, Western countries are operating in an effective manner for the construction of networks. The preeminent position held by the COVID-19 vaccine demonstrates that nation-states align with global authority regardless of the national context in which they operate. In sum, the policy agencies' citation networking practices have the potential to reveal global knowledge distribution structure as a proxy for the networking strategy that used for a pandemic.


 Citation

Please cite as:

PARK HW, YOON HY

Global COVID-19 Policy Engagement With Scientific Research Information: Altmetric Data Study

J Med Internet Res 2023;25:e46328

DOI: 10.2196/46328

PMID: 37384384

PMCID: 10365591

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