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Analyzing knowledge entities about COVID-19 using entitymetrics.
- Source :
- Scientometrics; May2021, Vol. 126 Issue 5, p4491-4509, 19p
- Publication Year :
- 2021
-
Abstract
- COVID-19 cases have surpassed the 109 + million markers, with deaths tallying up to 2.4 million. Tens of thousands of papers regarding COVID-19 have been published along with countless bibliometric analyses done on COVID-19 literature. Despite this, none of the analyses have focused on domain entities occurring in scientific publications. However, analysis of these bio-entities and the relations among them, a strategy called entity metrics, could offer more insights into knowledge usage and diffusion in specific cases. Thus, this paper presents an entitymetric analysis on COVID-19 literature. We construct an entity–entity co-occurrence network and employ network indicators to analyze the extracted entities. We find that ACE-2 and C-reactive protein are two very important genes and that lopinavir and ritonavir are two very important chemicals, regardless of the results from either ranking. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01389130
- Volume :
- 126
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Scientometrics
- Publication Type :
- Academic Journal
- Accession number :
- 150024550
- Full Text :
- https://doi.org/10.1007/s11192-021-03933-y