Analyzing the perceptions and images of traditional markets via online revie

Recently, in efforts to revitalize traditional markets, the Ministry of Culture, Sports and Tourism of South Korea has put forth the 'K-Tourism Market' project that seeks to develop entertainment, food, and other attractions and turn them into tour routes. Traditional markets are where local residents and tourists interact with one another and enjoy various social and economic benefits. Directing tourists to traditional markets can help address the population decline issue pervasive in South Korea. This study tried to understand the behaviors and preferences of tourists to traditional markets by examining their perceptions and images. To this end, Google online review data were collected and analyzed via big data analysis, frequency analysis, N-gram analysis, centrality analysis, and CONCOR cluster analysis. From this, four major clusters were identified. This study helped expand and enrich research methodology by conducting systematic big data analysis of online reviews from traditional market tourists. Furthermore, by identifying the needs and expectations of tourists, this study can help practitioners improve traditional market service and experience quality.