Awareness and resolution of touristification in Korea using social media big data analytics

Purpose: This study aimed to evaluate the resolution of touristification and the SNS user’s perception of the phenomenon through analysis of social big data. Design/methodology/approach: Data were collected from a "café" and a blog on social media platforms (Naver, Daum) that were collected as analysis channels. It was analyzed using social network analysis and semantic network analysis. Findings: Sixty of the 986 entries were selected using the keyword "touristification" for social media big data research. First, various keywords recognized by tourists, such as "tourist destination", "citizen", "gentrification", "phenomenon", "Bukchon", were extracted. Second, convergence of iteration correlation (CONCOR) analysis distinguished five groups. Research limitations/implications: The study assessed the implications of touristification’s resolution. This study used social big data before Covid-19, and there was a limit to sample collection. Originality/value: Existing studies related to touristification were conducted mainly on qualitative and empirical research, but this study expanded the research methodology to big data research that combines social network analysis and semantic network analysis.