التفاصيل البيبلوغرافية
| العنوان: |
Analyzing knowledge entities about COVID-19 using entitymetrics |
| المؤلفون: |
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 Zha |
| المصدر: |
Springer;Akadémiai Kiadó, Scientometrics. 126(5):4491-4509 |
| سنة النشر: |
2021 |
| الوصف: |
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. |
| نوع الوثيقة: |
redif-article |
| اللغة: |
English |
| DOI: |
10.1007/s11192-021-03933 |
| الإتاحة: |
https://ideas.repec.org/a/spr/scient/v126y2021i5d10.1007_s11192-021-03933-y.html |
| رقم الأكسشن: |
edsrep.a.spr.scient.v126y2021i5d10.1007.s11192.021.03933.y |
| قاعدة البيانات: |
RePEc |
