Tracking and Mining the COVID-19 Research Literature

Frontiers in Research Metrics and Analytics

卷:5

Yi Zhang¹  Mengjia Wu²  Ying Huang³  Alan L. Porter⁵ 

[1] Innovation Policy, Georgia Tech, Atlanta, GA, United States;

[2] D Monitoring (ECOOM), KU Leuven, Leuven, Belgium;

[3] Department of Management, Strategy and Innovation (MSI), Center for R&

[4] Faculty of Engineering and Information Technology, Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia;

[5] Science, Technology &

[6] Search Technology, Inc., Norcross, GA, United States;

关键词: text analysis;    tech mining;    bibliometrics;    COVID-19;    coronavirus;    pandemic;   

DOI  :  10.3389/frma.2020.594060

来源: DOAJ

【 摘 要 】

The unprecedented, explosive growth of the COVID-19 domain presents challenges to researchers to keep up with research knowledge within the domain. This article profiles this research to help make that knowledge more accessible via overviews and novel categorizations. We provide websites offering means for researchers to probe more deeply to address specific questions. We further probe and reassemble COVID-19 topical content to address research issues concerning topical evolution and emphases on tactical vs. strategic approaches to mitigate this pandemic and reduce future viral threats. Data suggest that heightened attention to strategic, immunological factors is warranted. Connecting with and transferring in research knowledge from outside the COVID-19 domain demand a viable COVID-19 knowledge model. This study provides complementary topical categorizations to facilitate such modeling to inform future Literature-Based Discovery endeavors.

【 授权许可】

Unknown