A Text Mining Approach to Covid-19 Literature

Fangyao Liu, Daji Ergu, Biao Li, Wei Deng, Zhengxin Chen, Guoqing Lu and Yong Shi
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Fangyao Liu: Key Laboratory of Electronic and Information Engineering, (Southwest Minzu University), State Ethnic Affairs Commission, P. R. China
Daji Ergu: Key Laboratory of Electronic and Information Engineering, (Southwest Minzu University), State Ethnic Affairs Commission, P. R. China
Biao Li: ��College of Business Administration, Southwest University of Finance and Economics, P. R. China
Wei Deng: ��Department of Computer Science, University of Nebraska at Omaha, USA
Zhengxin Chen: ��Department of Computer Science, University of Nebraska at Omaha, USA
Guoqing Lu: �Department of Biology and School of Interdisciplinary Informatics, University of Nebraska at Omaha, USA
Yong Shi: �Research Center on Fictitious Economy and Data Science, Chinese Academy of Science, P. R. China∥Key Lab of Big Data Mining and Knowledge Management, Chinese Academy of Science, P. R. China

International Journal of Information Technology & Decision Making (IJITDM), 2024, vol. 23, issue 04, 1427-1448

Abstract: The novel coronavirus disease — COVID-19 is a historic catastrophe that has caused many devastating impacts on human life and wellness. Researchers in academia and industry strive to understand the causes of this pandemic disease and find new therapeutics combating it. Consequently, the number of COVID-19 related publications increases rapidly, and it is too difficult for medical researchers and practitioners to keep up with the latest research and development. Literature filtering and categorization, and knowledge discovery can use text mining as a powerful tool. In this paper, we propose a text mining method to explore the categories of COVID-19 related themes and identify the standard methodologies that have been used. We discuss the potential limitations of this preliminary study and present future perspectives related to COVID-19 research. This paper provides an quantitative and qualitative mixed analysis example of using some research papers by data mining method to dig out several hidden information and set up a foundation for data scientists to develop more effective algorithms to deal with COVID-19 related problems.

Keywords: COVID-19; coronavirus; text mining; classification; future trend; systematic review (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219622022500870

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