원문정보
초록
영어
In this study, social network analysis was performed to compare and analyze changes in domestic tourism trends before and after the outbreak of COVID-19 in a situation where the damage to the tourism industry due to COVID-19 is increasing. Using Textom, a big data analysis service, data were collected using the keywords “travel destination” and “travel trend” based on the collection period of 2019 and 2020, when the epidemic spread to the world and became chaotic. After extracting a total of 80 key words through text mining, centrality was analyzed using NetDraw of Ucinet6, and clustered into 4 groups through CONCOR analysis. Through this, we compared and analyzed changes in domestic tourism trends before and after the outbreak of COVID-19, and it is judged to provide basic data for tourism marketing strategies and tourism product development in the post-COVID-19.
목차
1. INTRODUCTION
2. PREVIOUS RESEACH
3. RESEARCH METHOD
3.1 Research project
3.2 Data collection
3.3 Analysis Method
4. RESEARCH RESULTS
4.1 Keyword Frequency and TF-IDF Analysis
4.2 Semantic Network Analysis
4.3 CONCOR Analysis
5. CONCLUSION
REFERENCES