The Korean government (Ministry of Culture, Sports and Tourism, Ministry of Health and Welfare, and Ministry of Education) has framed policies and conducted many projects to encourage adolescents to be more physically active. Despite these efforts, the participation rate of physical activity in Korean adolescents keeps decreasing. Thus, the purpose of this study was to analyze the perception of sports and physical activity in Korean adolescents through big data analysis of the last 10 years and to provide research data and statistical direction with regard to sports and physical activity participation in Korean adolescents. For data collection, data from 1 January 2010 to 31 December 2019 were collected from Naver (NAVER Corp., Seongnam, Korea), Daum (Kakao Corp., Jeju, Korea), and Google (Alphabet Inc., Mountain View, CA, USA), which are the most widely used search engines in Korea, using TEXTOM 4.0 (The Imc Inc., Daegu, Korea), a big data collection and analysis solution. Keywords such as “adolescent + sports + physical activity” were used. TEXTOM 4.0 can generate various collection lists at once using keywords. Collected data were processed through text mining (frequency analysis, term frequency–inverse document frequency analysis) and social network analysis (SNA) (degree centrality, convergence of iterated correlations analysis) by using TEXTOM 4.0 and UCINET 6 social network analysis software (Analytic Technologies Corp., Lexington, KY, USA). A total of 9278 big data (10.36 MB) were analyzed. Frequency analysis of the top 50 terms through text mining showed exercise (872), mind (851), health (824), program (782), and burden (744) in a descending order. Term frequency–inverse document frequency analysis revealed exercise (2108.070), health (1961.843), program (1928.765), mind (1861.837), and burden (1722.687) in a descending order. SNA showed that the terms with the greatest degree of centrality were exercise (0.02857), program (0.02406), mind (0.02079), health (0.02062), and activity (0.01872) in a descending order. Convergence of the iterated correlations analysis indicated five clusters: exercise and health, child to adult, sociocultural development, therapy, and program. However, female gender, sports for all, stress, and wholesome did not have a high enough correlation to form one cluster. Thus, this study provides basic data and statistical direction to increase the rate of physical activity participation in Korean adolescents by drawing significant implications based on terms and clusters through bid data analysis.

中文翻译：

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韩国青少年体育活动的大数据分析。

韩国政府（文化，体育和旅游部，卫生和福利部以及教育部）制定了政策并开展了许多项目，以鼓励青少年更加积极地运动。尽管做出了这些努力，韩国青少年的体育锻炼参与率仍在下降。因此，本研究的目的是通过近10年的大数据分析来分析韩国青少年对体育和体育活动的看法，并提供有关韩国青少年体育和体育活动参与的研究数据和统计方向。为了收集数据，收集了2010年1月1日至2019年12月31日之间的数据，这些数据来自Naver（韩国城南市的NAVER公司），Daum（韩国济州的Kakao公司）和Google（Alphabet Inc.，加利福尼亚州山景城）美国），使用大数据收集和分析解决方案TEXTOM 4.0（韩国大邱的Imc Inc.）在韩国使用最广泛的搜索引擎。使用了诸如“青少年+体育+体育活动”之类的关键字。TEXTOM 4.0可以使用关键字一次生成各种集合列表。使用TEXTOM 4.0和UCINET 6社交网络分析软件（分析技术）通过文本挖掘（频率分析，词频-逆文档频率分析）和社交网络分析（SNA）（程度中心性，迭代相关分析的收敛性）来处理收集的数据。公司（美国肯塔基州列克星敦）。总共分析了9278个大数据（10.36 MB）。通过文本挖掘对前50个术语的频率分析显示，锻炼（872），思维（851），健康（824），程序（782）和负担（744）降序排列。术语频率-反向文档频率分析显示了锻炼（2108.070），健康（1961.843），程序（1928.765），头脑（1861.837）和负担（1722.687）的降序排列。SNA显示，具有最高集中度的术语是运动（0.02857），程序（0.02406），思维（0.02079），健康（0.02062）和活动（0.01872）降序排列。迭代相关性分析的收敛性显示了五个类别：运动与健康，儿童到成人，社会文化发展，治疗和计划。但是，女性，全民体育，压力和健康状况之间的相关性不足以形成一个集群。从而，