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KMID : 1143520210090030009
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Journal of Korean Society of Oral Health Science
2021 Volume.9 No. 3 p.9 ~ p.17
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Analysis on the Research Trends of KOHS Journal Papers using Topic Modeling
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Kim Jung-Sool
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Abstract
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Objectives: The purpose of this study was to analyze latent topics and topic networks of papers in The Korean Journal of Oral Health Science(KOHS) Journal.
Methods: We collected Korean abstracts and Conclusions of 159 papers in KOHS Journal from 2013 Vol.1.No.1 to 2020 Vol.1 No.4. We used Netminer(Ver.4) software(Cyram products) to extract topics based on latent Dirichlet allocation algorithm.
Results: We preprocessed by TF-IDF method and proposed word cloud figure, 6 topics were extracted by using from TF/IDF data. The most important topic were topic 3, that is, research on the oral health promotion practice and level of stress about the teenagers including collegians, and the next topic 4, topic 1, topic 6, topic 2, topic 5 in sequence.
Conclusions: We extracted 6 topics were the best number of topics reflected the main issues of KOHS Journa papers. So, we need to find a various concerns to develop KOHS Journal in growth.
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KEYWORD
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KOHS journal, LDA, Research trend, Text mining, Topic modeling
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