Synergistic networks of COVID-19’s top papers

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.

The Role of Islamic Ethic Investment in Aceh

“…This synergy between entrepreneurs and the government must also be supported by social networks and good work networks in collaborating. Synergy indicators and social network analysis (SNA), as practical tools, provide the possibility of explaining the pattern of scientific collaboration and visualization of network relations (Riahinia N, 2022).…”

A bibliometric analysis of domestic and international research on maker education in the post-epidemic era

“…Many of these topics are closely related to this research area, such as eco-entrepreneurship (Guleria and Kaur, 2021), innovation integration (Cui et al, 2022), smart education (Ma et al, 2022) and other related studies, which can provide Research on maker education useful references for the research on maker education. The importance and superiority of bibliometrics and its related methods are self-evident (Riahinia et al, 2022), which can provide a panoramic view and point out possible evolutionary directions to related studies in a very short period and promote innovation and communication to a great extent. As a research medium, it not only helps scholars in related fields to make judgments and choices based on various metrics but also promotes academic development in various research fields (Alam et al, 2022).…”

“…, 2022) and other related studies, which can provide useful references for the research on maker education. The importance and superiority of bibliometrics and its related methods are self-evident (Riahinia et al. , 2022), which can provide a panoramic view and point out possible evolutionary directions to related studies in a very short period and promote innovation and communication to a great extent.…”

Guest editorial: COVID-19 pandemic and health informatics part 3

“…Through bibliometric analysis and related techniques, researchers can gain insight into a particular research area's trends and essential elements. Continuing from the efforts of previous special issues on this topic (Li et al , 2021; Shueb et al , 2022; Loan and Shah, 2022; Riahinia et al , 2022; Zhu and Lei, 2022; Danesh et al , 2021; Saab et al , 2021; Allen, 2021), Khazaneha et al (2023) used the science mapping analysis approach and co-word analysis to explore and visualize research fields and the thematic evolution of the coronavirus. Yari Eili and Rezaeenour (2023) used process mining and other simulation techniques to study the effectiveness of COVID-19 prevention strategies on infection and mortality trends.…”