빅데이터 분석을 활용한 워터파크의 인식 및 이용행태 변화 분석- COVID-19 전후비교를 중심으로 -

Abstract

This study examined how COVID-19 caused changes in perception and it influenced behavioral changes. This study selected Waterpark, one of the tourism industries that has been hit hard since COVID-19, as the target site. This study was conducted by a big data analysis study. Data were collected by dividing into two the periods before COVID-19(2015-2019) and after (2020-2021). Frequency analysis, TF-IDF, N-GRAM, and emotion analysis were conducted using TEXTOM. Significant findings as a result of the analysis were that the amount of data has increased compared to the previous period despite restrictions on the use of water parks after COVID-19. It was confirmed that people’s interest in water parks did not decrease compared to before COVID-19. In addition, as a result of the analysis, it was confirmed that before COVID-19, there was a lot of interest in information about waterparks itself across the country, but after COVID-19, interest in the information that was clearly affected by COVID-19 such as masks and quarantine increased. In addition, due to changes in behavior, people prefer private spaces, outdoor spaces, and natural spaces that can be kept away from others even if they are expensive due to the influence of COVID-19. For this reason, existing waterparks need to strengthen safety rules for preventing infectious diseases above all else, and it seems necessary to instill awareness that waterparks are safe. In addition, it seems necessary to lower the density of the number of people inside the water park due to the limitation on the number of visitors. Implications of this study were to prepare improvement measures tailored to the changed expectations of tourists. Therefore, based on these results, it was expected to use important basic data that can support the standards of operation plans or design in waterparks in the future.