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토픽모델링을 이용한 비대면 신문 기사 키워드 분석.
- Source :
- Journal of the Korea Institute of Information & Communication Engineering; Nov2022, Vol. 26 Issue 11, p1751-1754, 4p
- Publication Year :
- 2022
-
Abstract
- The news articles collected with keyword “non faceto-face” were analyzed through topic modeling applied with LDA algorithm. In this study, collected articles were divided into two periods, period 1(the beginning of COVID-19 spread) and period 2(the end of COVID-19 spread), according to issued date of the articles. The articles of period 1 showed support for non-faceto-face treatment, smart library, the beginning of the online financial era, non-face-to-face entrance exam and employment, stock investment for main topic words. And the articles of period 2 showed conversion to non face-to-face classes, increasing unmanned stores, online finance, education industry, home treatment for main topic words. Also, further issues were discussed through visualization of topic words. These results provide evidence that education and unmanned business in non-face-to-face industries are growing. [ABSTRACT FROM AUTHOR]
- Subjects :
- COVID-19
TEXT mining
VISUALIZATION
ALGORITHMS
EMPLOYMENT
Subjects
Details
- Language :
- Korean
- ISSN :
- 22344772
- Volume :
- 26
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- Journal of the Korea Institute of Information & Communication Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 160571635
- Full Text :
- https://doi.org/10.6109/jkiice.2022.26.11.1751