Bibliometric Analysis of Worldwide Coronavirus Research based on Web of Sciencebetween 1970 and February 2020 مقالة

مؤلف: Khalili، Leila ؛ Sreekumar، M.G ؛

International Journal Of Information Science And Management January & June 2021,Volume 19 - Number 1 ، عالمي (Ministry of Science/ISC (‎17 صفحة - من 27 إلی 43 )

الکلمات المفتاحية: Density Coronavirus Centrality measures Coauthorship Social networkanalysis

خلاصة:

Researchers worldwide are striving hard to find a solution for the coronavirus pandemic and reduce the fatalities from this severe outbreak. The purpose of this article is to evaluate and visualize the published documents about coronavirus research, based on extracted data from Web of Science (WoS) citation database. The study used a bibliometric method and social network analysis. Data were collected using the WoS database on February 23, 2020, with 13252 records being retrieved and used as the study sample. Descriptive statistics were used in the bibliometric method and network analysis. Text Statistics Analyzer and ISI.exe were used to compute the number of authors per document. VOSviewer and UCINET were used respectively for visualization and for measuring the centrality and the density of networks. Study findings indicate the top actors of the scientific society (authors, institutions, countries) that had the most publication on coronavirus. Similarly, the top keywords used by authors were identified. Also, the density and centrality measures of co-authorship networks (degree, closeness, betweenness) for the top 10 authors, institutions, countries, and keywords were identified. The Journal of Virology had the highest number of published papers on coronavirus research. The study revealed that the leading researchers and institutions were mostly from the United States of America, England, China, Germany, Netherlands, France, Canada, Japan, South Korea, and Saudi Arabia.

ملخص الجهاز:

The purpose of this article is to evaluate and visualize the published documents about coronavirus research, based on extracted data from Web of Science (WoS) citation database. Also, the density and centrality measures of co-authorship networks (degree, closeness, betweenness) for the top 10 authors, institutions, countries, and keywords were identified. Keywords: Centrality Measures, Co-authorship, Coronavirus, Density, Social Network Analysis Introduction Human coronaviruses (HCoVs) were first observed in the 1960s among patients with the common cold (Su & et al. Previous studies (Bharvi, Garg & Bali, 2003; Glanzel & Schubert, 2004; Kronegger, Ferligoj & Doreian, 2011) indicate an increasing trend for collaboration in conducting research. Though Web of Science (Wos), the world renowned indexing system has reported 13252 documents on Coronavirus research (as on the date of this study), it is observed that the number of papers on biliometrics studies and social network analysis are found to be very few. Recorded data were analyzed using descriptive statistics to study 'documents' features; also social networks analysis was carried out using descriptive statistics for centrality measures (degree, closeness and betweenness) and density of network. Co-authorship Networks of 85 Countries Visualizing co-words on coronavirus In the current study author keywords was considered as the unit of analysis for presenting concepts represented by the document. Table 3 Density of Co-authorship Networks {مراجعه شود به فایل جدول الحاقی} Based on findings of the present study the top 10 authors with the highest centrality measures were identified.

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