Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/253320 
Authors: 
Year of Publication: 
2021
Citation: 
[Journal:] Global Business & Finance Review (GBFR) [ISSN:] 2384-1648 [Volume:] 26 [Issue:] 1 [Publisher:] People & Global Business Association (P&GBA) [Place:] Seoul [Year:] 2021 [Pages:] 68-78
Publisher: 
People & Global Business Association (P&GBA), Seoul
Abstract: 
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.
Subjects: 
Touristification
Social Media Big Data
Social Network Analysis
Semantic Network Analysis
Overtourism
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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