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Synergistic networks of COVID-19’s top papers
- Source :
- Library Hi Tech. 40:454-494
- Publication Year :
- 2021
- Publisher :
- Emerald, 2021.
-
Abstract
- PurposeSynergy indicators and social network analysis (SNA), as practical tools, provide the possibility of explaining the pattern of scientific collaboration and visualization of network relations. Recognition of scientific capacities is the basis of synergy. The present study aims to measure and discover the synergistic networks of COVID-19’s top papers at the level of co-authorship, countries, journals, bibliographic couples and titles.Design/methodology/approachThe synergy indicator, co-authorship co-citation network analysis methods were applied. The research population comprises COVID-19’s top papers indexed in Essential Science Indicator and Web of Science Core Collection 2020 and 2021. Excel 2016, UCINET 6.528.0.0 2017, NetDraw, Ravar Matrix, VOSviewer version 1.6.14 and Python 3.9.5 were applied to analyze the data and visualize the networks.FindingsThe findings indicate that considering the three possible possibilities for authors, countries and journals, more redundancy and information are created and potential for further cooperation is observed. The synergy of scientific collaboration has revealed that “Wang, Y,” “USA” and “Science of the Total Environment” have the most effective capabilities and results. “Guan (2020b)” and “Zhou (2020)” are bibliographic couplings that have received the most citations. The keywords “CORONAVIRUS DISEASE 2019 (COVID-19)” were the most frequent in article titles.Originality/valueIn a circumstance that the world is suffering from a COVID-19 pandemic and all scientists are conducting various researches to discover vaccines, medicines and new treatment methods, scientometric studies, and analysis of social networks of COVID-19 publications to be able to specify the synergy rate and the scientific collaboration networks, are not only innovative and original but also of great importance and priority; SNA tools along with the synergy indicator is capable of visualizing the complicated and multifaceted pattern of scientific collaboration in COVID-19. As a result, analyses can help identify existing capacities and define a new space for using COVID-19 researchers’ capabilities.
- Subjects :
- education.field_of_study
Computer science
business.industry
media_common.quotation_subject
Population
Library and Information Sciences
Python (programming language)
Space (commercial competition)
Data science
Visualization
Originality
Publishing
education
business
Social network analysis
computer
Information Systems
computer.programming_language
media_common
Network analysis
Subjects
Details
- ISSN :
- 07378831
- Volume :
- 40
- Database :
- OpenAIRE
- Journal :
- Library Hi Tech
- Accession number :
- edsair.doi...........a3004e18a8e4e37525b37a0711ddb9d2