Analyzing knowledge entities about COVID-19 using entitymetrics

Qi Yu, Qi Wang, Yafei Zhang, Chongyan Chen, Hyeyoung Ryu, Namu Park, Jae-Eun Baek, Keyuan Li, Yifei Wu, Daifeng Li, Jian Xu, Meijun Liu, Jeremy J. Yang, Chenwei Zhang, Chao Lu, Peng Zhang, Xin Li, Baitong Chen, Islam Akef Ebeid, Julia Fensel, Chao Min, Yujia Zhai, Min Song (), Ying Ding and Yi Bu ()
Additional contact information
Qi Yu: Shanxi Medical University
Qi Wang: Shanxi Medical University
Yafei Zhang: Shanxi Medical University
Chongyan Chen: University of Texas
Hyeyoung Ryu: University of Washington
Namu Park: Yonsei University
Jae-Eun Baek: Dae-Gu University
Keyuan Li: Indiana University
Yifei Wu: Tsinghua University
Daifeng Li: Sun Yat-Sen University
Jian Xu: Sun Yat-Sen University
Meijun Liu: Fudan University
Jeremy J. Yang: University of New Mexico
Chenwei Zhang: the University of Hong Kong
Chao Lu: Hohai University
Peng Zhang: Tsinghua University
Xin Li: Wuhan University
Baitong Chen: Shanghai University
Islam Akef Ebeid: University of Texas
Julia Fensel: Westlake High School
Chao Min: Nanjing University
Yujia Zhai: Wuhan University
Min Song: Yonsei University
Ying Ding: University of Texas
Yi Bu: Peking University

Scientometrics, 2021, vol. 126, issue 5, No 36, 4509 pages

Abstract: 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.

Keywords: COVID-19; Knowledge graph; Entity; Entitymetrics; Scientific publications; Bibliometrics (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11192-021-03933-y

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