Analysis of Issues in Dentistry Using Topic Modeling
문경희,
소속 상세정보
문경희 ( Moon Kyung-Hui ) - Jinju Health College Department of Dental Hygiene
Abstract
Objective: This study collected articles released by BIGKinds (www.bigkinds.or.kr), which is a big data service made available by the Korea Press Foundation, by applying search keywords including “corona“ and “dentistry“ from January 6, 2020 to June 30, 2021.
Methods: Data extracted using NetMiner (Cyram Inc., Seongnam, Korea) was subject to a refining process to extract only keywords with a Term Frequency-Inverse Document Frequency coefficient of 0.5 or higher and Latent Dirichlet Allocation topic modeling was performed to derive the topics.
Results: Of the 5 derived topics, the topic accounting for the greatest portion was “vaccination”, followed by “dental health care”, “medical industry”, “time of confusion during the COVID-19 pandemic”, and “changes in daily life during the COVID-19 pandemic”.
Conclusion: The biggest issue in the dental sector in 2020 and the first half of 2021 due to the spread of COVID-19 were found to be “vaccination”, “dental health care”, “medical industry”, “time of confusion during the COVID-19 pandemic”, and “changes in daily life during the COVID-19 pandemic”. In the future, research should be conducted to better understand changes in the dental sector and plans for systematically resolving such issues.
키워드
dentistry; COVID-19; news articles; topic modeling
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