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A Bibliometric Network Analysis of Coronavirus during the First Eight Months of COVID-19 in 2020

Leonardo B. Furstenau, Bruna Rabaioli, Michele Kremer Sott, Danielli Cossul, Mariluza Sott Bender, Eduardo Moreno Júdice De Mattos Farina, Fabiano Novaes Barcellos Filho, Priscilla Paola Severo, Michael S. Dohan and Nicola Luigi Bragazzi
Additional contact information
Leonardo B. Furstenau: Graduate Program of Industrial Systems and Processes, University of Santa Cruz do Sul, Santa Cruz do Sul 96816-501, Brazil
Bruna Rabaioli: Department of Medicine, University of Santa Cruz do Sul, Santa Cruz do Sul 96816-501, Brazil
Michele Kremer Sott: Graduate Program of Industrial Systems and Processes, University of Santa Cruz do Sul, Santa Cruz do Sul 96816-501, Brazil
Danielli Cossul: Department of Psychology, University of Santa Cruz do Sul, Santa Cruz do Sul 96816-501, Brazil
Mariluza Sott Bender: Multiprofessional Residency Program in Urgency and Emergency, Santa Cruz Hospital, Santa Cruz do Sul 96810-072, Brazil
Eduardo Moreno Júdice De Mattos Farina: Scientific Writing Office Department, Higher School of Sciences of Santa Casa de Misericórdia de Vitória, Vitória 29025-023, Brazil
Fabiano Novaes Barcellos Filho: Scientific Writing Office Department, Higher School of Sciences of Santa Casa de Misericórdia de Vitória, Vitória 29025-023, Brazil
Priscilla Paola Severo: Graduate Program in Law, University of Santa Cruz do Sul, Santa Cruz do Sul 96816-501, Brazil
Michael S. Dohan: Faculty of Business Administration, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
Nicola Luigi Bragazzi: Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada

IJERPH, 2021, vol. 18, issue 3, 1-24

Abstract: The COVID-19 pandemic has affected all aspects of society. Researchers worldwide have been working to provide new solutions to and better understanding of this coronavirus. In this research, our goal was to perform a Bibliometric Network Analysis (BNA) to investigate the strategic themes, thematic evolution structure and trends of coronavirus during the first eight months of COVID-19 in the Web of Science (WoS) database in 2020. To do this, 14,802 articles were analyzed, with the support of the SciMAT software. This analysis highlights 24 themes, of which 11 of the more important ones were discussed in-depth. The thematic evolution structure shows how the themes are evolving over time, and the most developed and future trends of coronavirus with focus on COVID-19 were visually depicted. The results of the strategic diagram highlight ‘CHLOROQUINE’, ‘ANXIETY’, ‘PREGNANCY’ and ‘ACUTE-RESPIRATORY-SYNDROME’, among others, as the clusters with the highest number of associated citations. The thematic evolution. structure presented two thematic areas: “Damage prevention and containment of COVID-19” and “Comorbidities and diseases caused by COVID-19”, which provides new perspectives and futures trends of the field. These results will form the basis for future research and guide decision-making in coronavirus focused on COVID-19 research and treatments.

Keywords: COVID-19; coronavirus; pandemics; virus diseases; co-word analysis; strategic intelligence; bibliometric analysis; SciMAT (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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