→ 한국식품과학회지2019 ; 51(2): 176-181
Analysis of dieting practices in 2016 using big data
빅데이터를 통한 2016년의 다이어트 실태 분석
Eun-Jin Jung1, Un-Jae Chang1, and Kyungae Jo2,*
1Department of Food & Nutrition, DongDuk Women’s University, 2College of Health Science, Korea University
1동덕여자대학교 식품영양학과, 2고려대학교 보건과학대학
The aim of this study was to analyze dieting practices and tendencies in 2016 using big data. The keywords related to diet were collected from the portal site Naver and analyzed through simple frequency, N-gram, keyword network, and analysis of seasonality. The results showed that exercise had the highest frequency in simple frequency analysis. However, diet menu appeared most frequently in N-gram analysis. In addition, analysis of seasonality showed that the interest of subjects in diet increased steadily from February to July and peaked in October 2016. The monthly frequency of the keyword highfat diet was highest in October, because that showed the ‘Low Carbohydrate High Fat’ TV program. Although diet showed a certain pattern on a yearly basis, the emergence of new trendy diets in mass media also affects the pattern of diet. Therefore, it is considered that continuous monitoring and analysis of diet is needed rather than periodic monitoring.
big data, diet menu, exercise, commercial diet, continuous monitoring
한국식품과학회지 2019 Apr; 51(2): 176 - 181