earticle

영어

This study examined xenophobia as perceived by local residents of tourist destinations and in the era of overtourism and during the COVID-19 pandemic to determine its implications on the tourism sector. Text mining techniques were used in the analysis and, through clustering analysis and emotional analysis, an in-depth examination of the xenophobia phenomenon perceived by local residents for both periods was conducted. The result of the analysis showed that local residents expressed xenophobia toward tourists in the overtourism situation and the COVID-19 situation. However, it was recognized that the intensity of expression was organically and flexibly controlled according to various factors and timings due to tourism overcrowding or stagnation and certain environmental situations caused by external factors. This means that the perception of xenophobia and tourism revitalization always coexist among local residents and it can be approached from the perspective balance and control. Therefore, a balance of the xenophobia phenomenon of local residents by inducing win-win growth in times of overcrowding in tourism such as overtourism is necessary. In times of tourism stagnation, such as the COVID-19 period, balancing efforts through proper distribution with activation are needed. Theoretically, the approach to studying xenophobia was diversified, contributing to the theoretical and external expansion. The big data analysis method was also used to contribute to methodological expansion. Practically, the analysis of the phenomenon provided a means of deriving national policies and preparing countermeasures. It also laid the foundation for maintaining the sustainability of tourist destinations.