한국융합학회논문지 (Journal of the Korea Convergence Society)

  • 제12권6호
  • /
  • Pages.233-239
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  • 2021
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  • 2233-4890(pISSN)
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  • 2713-6353(eISSN)
한국융합학회 (Korea Convergence Society)
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신문 빅데이터와 키워드 분석을 이용한 홈트레이닝 트렌드 분석

Home training trend analysis using newspaper big data and keyword analysis

  • 지동철 (고려대학교 스포츠융합학과) ;
  • 김상호 (고려대학교 국제스포츠학부)
  • 투고 : 2021.03.15
  • 심사 : 2021.06.20
  • 발행 : 2021.06.28
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초록

최근 코로나19(COVID-19)라는 신종 바이러스로 인해 사람들은 외출을 자제하고 집안에 있는 시간이 길어졌다. 그로 인해 활동량이 급감하고 체중이 증가하여 건강에 대한 관심이 더욱 높아졌고, 이를 해결하기 위한 방법으로 홈트레이닝이 대안이 될 수 있다. 이에 홈트레이닝의 트렌드를 알아보기 위해 뉴스분석시스템인 빅카인즈(BIG KINDS)에서 제공하는 뉴스를 활용하여 2019년 12월 1일부터 2020년 11월 30일까지의 기사를 수집하였다. 빈도분석, 가중도에 따른 관계도 분석, 연관어 분석을 실시하였고, 빅카인즈에서 개발한 알고리즘을 활용한 프로그램으로 분석을 실시하였다. 결론적으로 첫째, 홈트레이닝은 인공지능의 기술과 등장이 홈트레이닝을 주도하는 것으로 나타났다. 둘째, 홈트레이닝은 이동통신사의 관련한 컨텐츠와 영상서비스 위주로 이루어지고 있음을 추측할 수 있다. 셋째, 운동 종목으로는 필라테스의 선호도가 높고, 이와 관련된 운동용품의 수요가 증가함에 따라 상표출원도 영향이 있음을 알 수 있었다. 다음연구에서는 연구방법론을 보완하고 다양한 분석을 통해 향후 시행될 여러 빅데이터 연구의 기초자료로 활용될 것을 기대한다.

Recently, the COVID-19 virus has caused people to stay indoors longer without going out. As a result of this, people's activity decreased sharply, and their weight gained. So people became more interested in health. Home training can be an alternative method to solve this problem. Accordingly, To find out the trends of home training, we collected articles from December 1, 2019, to November 30, 2020, using the news provided by BIG KINDS, a news analysis system. We analyzed frequency analysis, relational analysis according to weighting, and related word analysis with the program using the algorithm developed by BIG KINDS. In conclusion, first, it was found that home training is led by technology and the emergence of artificial intelligence. Second, it can be assumed that people mainly do home training using content and video services related to mobile carriers. Third, people had a high preference for Pilates in the sports category. It can be seen that the number of patent applications increased as the demand for exercise products related to Pilates increased. In the next study, we expect that this study will be used as primary data for various big data studies by supplementing the research methodology and conducting various analyses.

키워드

참고문헌

  1. S. H. Jun & J. H. Kim. (2020). Theoretical Background and Prospects for the Untact Industry. Journal of New Industry and Business, 38(1), 96-116. DOI : 10.30753/EMR.2020.38.1.005
  2. T. W. Kim. (2020). Issue & Focus, 385, 1-8. Sejong : KIHASA.
  3. K. O. Kim & S. B. Kim. (2020). Review of Sports in the Era of New Normal. The Korea Journal of Sport, 18(3), 793-801. DOI : 10.46669/KSS.2020.18.3.072
  4. M. J. Seong. (2020). Sport Science, 151, 2-9. Seoul : Korea Institute of Sport Science.
  5. J. E. Lee. (2020. 4. 24), 'The amount of activity decreased and the amount of sleep increased'...Corona's Changing Daily Life. Newsis. https://newsis.com/view/?id=NISX20200423_0001004447&cID=13001&pID=13000
  6. M. Hamer, C. R. Gale, M. Kivimaki & G. D. Batty. (2020). Overweight, obesity, and risk of hospitalization for COVID-19: A community-based cohort study of adults in the United Kingdom, Proceedings of the National Academy of Sciences of the United States of America, 117(35), 21011-21013. DOI : 10.1073/PNAS.2011086117
  7. S. E. Kim. (2019). The Relationship between Mentoring and Exercise Immersion and Exercise Intention of Home Training Leaders. The Korea Journal of Sport, 17(4), 751-762.
  8. Y. J. Lee & S. T. Byun. (2016). A Study on Application Design for Home Fitness Wearable Devices, Society of Korea Illusart, 19(4), 169-178.
  9. Y. S. Kim, T. H. Kim, S. J. Park, C. Y. Lee & H. J. Jung. (2019). A Case Study on the Management of Medical and Health Care Services in the Age of Uncontact and Improvement, The Korea Producction And Operations Management Society, 89-90.
  10. T. Y. Ha & H. J. Lee. (2019). Presenting Direction for the Implementation of Personal Movement Trainer through Artificial Intelligence based Behavior Recognition, Journal of the Korea Convergence Society, 10(6), 235-242. DOI : 10.15207/JKCS.2019.10.6.235
  11. D. H. Kim. (2020). A Study on the Untact Dance Practical Classes in Universities in the COVID-19 Era, The Korean Society of Dance, 78(5), 37-61. DOI : 10.21317/KSD.78.5.3
  12. S. H. Jun & J. H. Kim. (2020). Theoretical Background and Prospects for the Untact Industry. Journal of New Industry and Business, 38(1), 96-116. https://doi.org/10.30753/EMR.2020.38.1.005
  13. U. S. Hwang. (2020). An Analysis of the Trends of Interrest in Commercial Education by Big Data Application. The Korean Academy of Business Education 34(1), 1-22. DOI : 10.34274/KRABE.2020.34.1.001
  14. K. H. Kim, H. W. Byun. (2020). The Analysis of Fashion Trend Cycle using Big Data, Journal of the Korea Convergence Society, 11(2), 113-123. DOI : 10.15207/JKCS.2020.11.12.113
  15. J. M. Lee, J. H. Lee & M. J. Kim. (2017). A Study on Perception of Ski Resort Using Big Data Analysis, The Korean Journal of Physical Education, 56(4), 415-430.
  16. J. S. Kim. (2018). A Study on the Perception of Fashion Streaming Service Using Text Mining Analysis, Journal of Fashion Design, 18(1), 107-118. DOI : 10.18652/2018.18.1.7
  17. M. J. Kim. (2020). Analyzing the Trend of Wearable Keywords using Text-mining Methodology, Journal of Digital Convergence, 18(9), 181-190. https://doi.org/10.14400/JDC.2020.18.9.181
  18. S. Kyun, H. Kim & S. Y. Lee. (2019). Analyzing the Keywords of Future Education using Text-mining Methodology, Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, ane Sociology, 9(5), 11-23. DOI : 10.21742/AJMAHS.201905.02
  19. S. Y. Hong. (2020). An Analysis on the Predictor Keyword of Successful Aging: Focused on Data Mining, Journal of the Korean Contents Association, 20(3), 223-234. DOI : 10.5392/JKCA.2020.20.03.223
  20. BIG KINDS. (2020). https://www.bigkinds.or.kr/v2/news/index.do
  21. E. J. Jung & U. J. Chang. (2016). Tendency and Network Analysis of Diet Using Big Data, Journal of the Korean Dietetic Association, 22(4), 310-319. DOI : 10.14373/FKDA.2016.22.4.310
  22. J. A. Jeon. (2020). A Study on the Change of Camping Trends through Big Data, Tourism Research, 45(3), 443-463. https://doi.org/10.32780/KTIDOI.2020.45.3.443
  23. S. H. Kim. (2020. 4. 20), Practice distance and lose belly fat following the AI coach. Kmib. http://news.kmib.co.kr/article/view.asp?arcid=0924133721&code=11161100
  24. Y. J. Cho. (2020. 4. 1), Home training game fever brought by Corona 19. Do you have any other alternatives. DongA. http://www.donga.com/news/article/all/20200401/100453244/1
  25. Y. J. Kim. (2020). NCONTENT, 15, 30-32 Naju : KCCA
  26. J. W. Han. (2020. June). Home Training Era to Learn Exercise on YouTube, SAMTOH, 99-99.
  27. O. J. Kwon. (2020). A Case Study of Changes in the Exercise Behavior of the Elderly by COVID-19, Korean Journal of Sport Psychology, 31(2),, 123-134. https://doi.org/10.14385/KSSP.31.2.123
  28. E. J. Jung & U. J. Chang. (2016). Tendency and Network Analysis of Diet Using Big Data, Journal of the Korean Dietetic Association, 22(4), 310-319. DOI : 10.14373/FKDA.2016.22.4.310
  29. M. A. Kang & S. U. Nam. (2020). An exploratory study On-line class, a future education method: Based on FGI study on elementary school teachers in Seong-si, Journal of Learner-Centered Curriculum and Instruction, 20(21), 89-116. DOI : 10.22251/jlcci.2020.20.21.89
  30. J. H. Park. (2020). A Comparative Study on the 'Corona19' News Frame Based on Ideological Orientation of Media, Korean Journal of Journalism & Communication Studies, 64(4), 40-85. https://doi.org/10.20879/kjjcs.2020.64.4.002