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http://dx.doi.org/10.17661/jkiiect.2022.15.5.423

Research Topic Analysis of the Domestic Papers Related to COVID-19 Using LDA  

Kim, Eun-Hoe (Department of Software Engineering, Seoil University)
Suh, Yu-Hwa (Baird University College, Soongsil University)
Publication Information
The Journal of Korea Institute of Information, Electronics, and Communication Technology / v.15, no.5, 2022 , pp. 423-432 More about this Journal
Abstract
This paper analyzes a total of 10,599 papers related to COVID-19 from January 2020 to July 2022 collected from the KCI site using LDA topic modeling so that academic researchers can understand the overall research trend. The results of LDA topic modeling are analyzed by major research categories so that academic researchers can easily figure out topics in their research fields. Then, the detailed research category information in which a lot of research is done by topic is analyzed. It is very important for academic researchers to understand the trend of research topics over time. Therefore, in this paper, the trend of topics is analyzed and presented using time series decomposition.
Keywords
COVID-19; LDA; Research Topic; Topic Modeling; Time Series Decompose;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
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