텍스트 마이닝을 이용한 코로나19 전후 청소년과 식생활 관련 키워드 검색 경향 분석

Abstract

This study analyzed Naver, Daum, Google, YouTube, and Twitter using TEXTOM for two years and four years as of January 18, 2020. The results are as follows. First, the total number and volume of keyword search data related to youth and diet were slightly higher after COVID-19, showing that interest increased due to COVID-19. Second, as a result of frequency analysis, ‘education’ was the highest before COVID-19, and ‘health’ was the highest after COVID-19, showing that interest in health is increasing due to the increased importance of health and immunity due to COVID-19. Third, as a result of frequency weight analysis of the top 50 keywords, ‘education’ showed the highest frequency before COVID-19, and ‘acne’ after COVID-19. Fourth, the results visualized using word cloud showed that the keywords ‘education’ before COVID-19 and ‘health’ after COVID-19 appeared the largest and boldest, showing the highest frequency and importance. As a result of the above results, we were able to use the text mining method to apply it to eating habits, and we used materials visualized as a highly readable word cloud in units such as eating problems in adolescence and balanced meal planning and selection in the home economics curriculum to improve the teaching of the class. The direction of proper eating habits education, including using it as a medium, was presented.