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Bibliometric Analysis of Worldwide Coronavirus Research based on Web of Science between 1970 and February 2020

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dc.contributor.author Khalili, Leila
dc.contributor.author Sreekumar, M.G.
dc.date.accessioned 2020-09-10T10:36:57Z
dc.date.available 2020-09-10T10:36:57Z
dc.date.issued 2020
dc.identifier.uri http://hdl.handle.net/2259/1045
dc.description International Journal of Information Science and Management Vol. 19, No. 1, 2021, 27-43 en_US
dc.description.abstract Researchers all over the world are striving hard to find a solution for the coronavirus pandemic and reduce the fatalities from this severe outbreak. The paper aims to study the characteristics of coronavirus publications based on bibliometrics and social network analysis. The study used bibliometric method and social network analysis. Data were collected using Web of Science (WoS) database on 23 February 2020, with 13252 records being retrieved and used as study sample. Descriptive statistics were used in bibliometric method and network analysis. Text Statistics Analyzer and ISI.exe were used to compute the number of author per documents. VOSviewer and UCINET were used respectively for visualization and for measuring the centrality as well as density of networks. Study findings indicate top 10 actors of scientific society (authors, institutions, countries) that had the most publication on coronavirus. Similarly top 10 keywords used by authors were identified. Also the density and centrality measures of co-authorship networks (degree, closeness, betweenness) for top 10 authors, institutions, countries and keywords were identified. Journal of Virology had the highest number of published documents on coronavirus research. Doing effective research projects require knowledge of key actors of each scientific domain and their position in the network. 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. en_US
dc.language.iso en en_US
dc.subject Centrality Measures en_US
dc.subject Co-authorship en_US
dc.subject Coronavirus en_US
dc.subject Density en_US
dc.subject Social Network Analysis en_US
dc.title Bibliometric Analysis of Worldwide Coronavirus Research based on Web of Science between 1970 and February 2020 en_US
dc.title.alternative Bibliometric Analysis of Coronavirus Research en_US
dc.type Article en_US

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  • Journal Articles [15]
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