빅데이터를 활용한 홈트레이닝 인식 분석 : COVID-19 확산시점을 중심으로

Abstract

The purpose of this study was to examine the awareness of home training focusing on the spread of COVID-19 to use big data techniques based on big data. As a keyword for data search, ‘COVID-19 home training’ was searched as a keyword, and the top 30 keyword were analyzed to compensate for the limitations of network simplification and network visualization centering on important nodes in entire network. The data analysis period was conducted from April 4 to October 4, 2020 because of the point of spread of COVID-19, and the semantic connection network and N-gram network analysis were conducted in stages. The main analysis results of the study were as follows. First, looking at the top 10 words extracted based on the keyword of COVID-19 home training, home training (2,791), Corona19 (2,036), exercise (1,101), living only at home (1045), non-face-to-face exercise (567), visited PT (440), health promotion (409), health (402), application (397), recommended for one day (395). Second, as a result of conducting N-gram network craft, Corona19/home training (523), home training/overcoming (288), home training/Corona19 (244), Corona19/non-face-to-face exercise (201), home training/diet (195), social/injury (192), senior/home training(189), diet/elderly(189), home training/trainer(166), smart home training home training(163). At the time of the spread of Corona19, we were able to explore how home training was perceived.