Key Attributes and Clusters of the Korean Exercise Healthcare Industry Viewed through Big Data: Comparison before and after the COVID-19 Pandemic
This study aims to predict the characteristics of the exercise healthcare industry in the post-pandemic era by comparing the periods before and after the coronavirus disease 2019 outbreak through big data analysis. TEXTOM, the Korean big data collection and analysis solution, was used for data colle...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/11/15/2133 |
| _version_ | 1797586740107542528 |
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| author | Sung-Un Park Deok-Jin Jang Dong-Kyu Kim Chulhwan Choi |
| author_facet | Sung-Un Park Deok-Jin Jang Dong-Kyu Kim Chulhwan Choi |
| author_sort | Sung-Un Park |
| collection | DOAJ |
| description | This study aims to predict the characteristics of the exercise healthcare industry in the post-pandemic era by comparing the periods before and after the coronavirus disease 2019 outbreak through big data analysis. TEXTOM, the Korean big data collection and analysis solution, was used for data collection. The pre-pandemic period was defined as 1 January 2018–31 December 2019 and the pandemic period as 1 January 2020–31 December 2021. The keywords for data collection were “exercise + healthcare + industry”. Text mining and social network analysis were conducted to determine the overall characteristics of the Korean exercise healthcare industry. We identified 30 terms that appeared most frequently on social media. Four common (<i>smart management</i>, <i>future technology</i>, <i>fitness</i>, and <i>research</i>) and six different clusters (<i>sports education</i>, <i>exercise leader</i>, <i>rehabilitation</i>, <i>services</i>, <i>business</i>, and <i>COVID-19</i>) were obtained for the pre-pandemic and pandemic periods. <i>Smart management</i>, <i>future technology</i>, <i>fitness</i>, and <i>research</i> are still important values across both periods. The results provide meaningful data and offer valuable insights to explore the changing trends in exercise healthcare. |
| first_indexed | 2024-03-11T00:27:23Z |
| format | Article |
| id | doaj.art-6a2d3eb90499487b92bada3e26b60012 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-11T00:27:23Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-6a2d3eb90499487b92bada3e26b600122023-11-18T22:56:04ZengMDPI AGHealthcare2227-90322023-07-011115213310.3390/healthcare11152133Key Attributes and Clusters of the Korean Exercise Healthcare Industry Viewed through Big Data: Comparison before and after the COVID-19 PandemicSung-Un Park0Deok-Jin Jang1Dong-Kyu Kim2Chulhwan Choi3Department of Sports and Health, Hwasung Medi-Science University, Hwaseong-si 18274, Republic of KoreaDepartment of Sports Medicine, Shinhan University, Uijeongbu-si 11644, Republic of KoreaDepartment of Sports Science, Chungwoon University, Hongseong-gun 32224, Republic of KoreaDepartment of Physical Education, Gachon University, Seongnam-si 13120, Republic of KoreaThis study aims to predict the characteristics of the exercise healthcare industry in the post-pandemic era by comparing the periods before and after the coronavirus disease 2019 outbreak through big data analysis. TEXTOM, the Korean big data collection and analysis solution, was used for data collection. The pre-pandemic period was defined as 1 January 2018–31 December 2019 and the pandemic period as 1 January 2020–31 December 2021. The keywords for data collection were “exercise + healthcare + industry”. Text mining and social network analysis were conducted to determine the overall characteristics of the Korean exercise healthcare industry. We identified 30 terms that appeared most frequently on social media. Four common (<i>smart management</i>, <i>future technology</i>, <i>fitness</i>, and <i>research</i>) and six different clusters (<i>sports education</i>, <i>exercise leader</i>, <i>rehabilitation</i>, <i>services</i>, <i>business</i>, and <i>COVID-19</i>) were obtained for the pre-pandemic and pandemic periods. <i>Smart management</i>, <i>future technology</i>, <i>fitness</i>, and <i>research</i> are still important values across both periods. The results provide meaningful data and offer valuable insights to explore the changing trends in exercise healthcare.https://www.mdpi.com/2227-9032/11/15/2133exercisehealthcaretechnologyCOVID-19 |
| spellingShingle | Sung-Un Park Deok-Jin Jang Dong-Kyu Kim Chulhwan Choi Key Attributes and Clusters of the Korean Exercise Healthcare Industry Viewed through Big Data: Comparison before and after the COVID-19 Pandemic Healthcare exercise healthcare technology COVID-19 |
| title | Key Attributes and Clusters of the Korean Exercise Healthcare Industry Viewed through Big Data: Comparison before and after the COVID-19 Pandemic |
| title_full | Key Attributes and Clusters of the Korean Exercise Healthcare Industry Viewed through Big Data: Comparison before and after the COVID-19 Pandemic |
| title_fullStr | Key Attributes and Clusters of the Korean Exercise Healthcare Industry Viewed through Big Data: Comparison before and after the COVID-19 Pandemic |
| title_full_unstemmed | Key Attributes and Clusters of the Korean Exercise Healthcare Industry Viewed through Big Data: Comparison before and after the COVID-19 Pandemic |
| title_short | Key Attributes and Clusters of the Korean Exercise Healthcare Industry Viewed through Big Data: Comparison before and after the COVID-19 Pandemic |
| title_sort | key attributes and clusters of the korean exercise healthcare industry viewed through big data comparison before and after the covid 19 pandemic |
| topic | exercise healthcare technology COVID-19 |
| url | https://www.mdpi.com/2227-9032/11/15/2133 |
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