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COVID-19 전후 국내관광 인식 변화 - 소셜미디어 빅데이터 분석을 중심으로 -

Changes in Domestic Tourism Perception Before and After COVID-19 - Focusing on Social Media Big Data Analysis -

이주양|장필식
한국외식산업학회 (The Korean Foodservice Association)|2024.12|한국외식산업학회지 (FoodService Industry Journal)|제20권 제6호|pp. 209-224|DOI 10.22509/kfsa.2024.20.6.014

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키워드

COVID-19Social MediaDomestic TourismBig Data AnalysisTourism Perception
주제분류관광학

초록

This study systematically analyzed the impact of the unprecedented COVID-19 pandemic on domestic tourism perception in Korea. The research collected and analyzed text data related to 'domestic tourism' and 'domestic travel' from Naver, Daum and Google social media platforms across three periods: pre-COVID-19(2018-2019), during COVID-19 (2020-2021), and post-COVID-19 (2022-2023), focusing on changes in tourism discourse and behavior patterns.The methodology employed three comprehensive analytical approaches. TF-IDF analysis identified changes in keyword importance and temporal relevance. Centrality analysis examined changes in keyword connectivity and mediation roles, revealing evolving relationship structures within tourism discourse. CONCOR analysis derived characteristics and patterns of keyword clusters across different periods, highlighting structural changes in tourism perceptions. The findings revealed significant changes in domestic tourism perception around COVID-19. The pre-pandemic patterns centered on cafe culture and family-oriented travel shifted to safety and pristine tourist destinations during the pandemic. Tourist behavior showed increased preference for small-group travel and natural attractions, particularly focusing on Jeju Island. Post-pandemic, a new tourism paradigm emerged, maintaining safety awareness while pursuing unrestricted travel and diverse experiential activities. The analysis also indicated increased interest in personalized travel experiences and digital information platforms. This study holds academic significance in empirically verifying tourism perception changes through big data analysis, contributing to the understanding of crisis-induced behavioral changes in tourism. Practical implications include the need for developing tourism products considering safety and hygiene, planning small-group customized products, strengthening digital information systems, and developing experience-based content highlighting regional characteristics. These findings can serve as valuable foundational data for establishing tourism policies and developing new marketing strategies in the post-COVID era.

Abstract

This study systematically analyzed the impact of the unprecedented COVID-19 pandemic on domestic tourism perception in Korea. The research collected and analyzed text data related to 'domestic tourism' and 'domestic travel' from Naver, Daum and Google social media platforms across three periods: pre-COVID-19(2018-2019), during COVID-19 (2020-2021), and post-COVID-19 (2022-2023), focusing on changes in tourism discourse and behavior patterns.The methodology employed three comprehensive analytical approaches. TF-IDF analysis identified changes in keyword importance and temporal relevance. Centrality analysis examined changes in keyword connectivity and mediation roles, revealing evolving relationship structures within tourism discourse. CONCOR analysis derived characteristics and patterns of keyword clusters across different periods, highlighting structural changes in tourism perceptions. The findings revealed significant changes in domestic tourism perception around COVID-19. The pre-pandemic patterns centered on cafe culture and family-oriented travel shifted to safety and pristine tourist destinations during the pandemic. Tourist behavior showed increased preference for small-group travel and natural attractions, particularly focusing on Jeju Island. Post-pandemic, a new tourism paradigm emerged, maintaining safety awareness while pursuing unrestricted travel and diverse experiential activities. The analysis also indicated increased interest in personalized travel experiences and digital information platforms. This study holds academic significance in empirically verifying tourism perception changes through big data analysis, contributing to the understanding of crisis-induced behavioral changes in tourism. Practical implications include the need for developing tourism products considering safety and hygiene, planning small-group customized products, strengthening digital information systems, and developing experience-based content highlighting regional characteristics. These findings can serve as valuable foundational data for establishing tourism policies and developing new marketing strategies in the post-COVID era.

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