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http://dx.doi.org/10.5762/KAIS.2021.22.5.354

A Study on the Factors of Well-aging through Big Data Analysis : Focusing on Newspaper Articles  

Lee, Chong Hyung (Department of Hospital Management, Konyang University)
Kang, Kyung Hee (Department of Dental Hygiene, Konyang University)
Kim, Yong Ha (Department of Hospital Management, Konyang University)
Lim, Hyo Nam (College of Nursing, Konyang University)
Ku, Jin Hee (Division of Software Liberal Arts, Stokes College, Mokwon University)
Kim, Kwang Hwan (Department of Hospital Management, Konyang University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.22, no.5, 2021 , pp. 354-360 More about this Journal
Abstract
People hope to live a healthy and happy life achieving satisfaction by striking a good work-life balance. Therefore, there is a growing interest in well-aging which means living happily to a healthy old age without worry. This study identified important factors related to well-aging by analyzing news articles published in Korea. Using Python-based web crawling, 1,199 articles were collected on the news service of portal site Daum till November 2020, and 374 articles were selected which matched the subject of the study. The frequency analysis results of text mining showed keywords such as 'elderly', 'health', 'skin', 'well-aging', 'product', 'person', 'aging', 'female', 'domestic' and 'retirement' as important keywords. Besides, a social network analysis with 45 important keywords revealed strong connections in the order of 'skin-wrinkle', 'skin-aging' and 'old-health'. The result of the CONCOR analysis showed that 45 main keywords were composed of eight clusters of 'life and happiness', 'disease and death', 'nutrition and exercise', 'healing', 'health', and 'elderly services'.
Keywords
Well-aging; Old Age; Big Data; Text Mining; Social Network Analysis; CONCOR Analysis;
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