Big data analysis of Korean travelers’ behavior in the post-COVID-19 era

Abstract

Due to the spread of COVID-19 worldwide in 2020, the tourism industry is facing a calamitous crisis as migration and travel between the countries has been restricted. The purpose of this study is to explore changes in Korean tourism behavior after COVID-19. Korean social media data was collected from the World Health Organization’s declaration of a public health emergency of international concern, in January 2020, to August 2020, the summer vacation season. Keywords were extracted via text mining, and the current perspectives of Koreans concerning tourism that manifest content analysis were investigated. In addition, UCINET 6 was used to visualize related words by conducting centrality analysis, CONCOR (CONvergent CORrelation) analysis, and semantic system network analysis. The analysis showed that Korean tourists have increased their preference for domestic travel, and showed interest in government subsidies. Korean tourists also showed greater interest in eco-trips and gourmet trips. Although this study is limited to Korea, it can be used as a regional strategy.