초록 열기/닫기 버튼
The purpose of this study was to explore awareness of food tourism using big data analysis. This study collected corpus data related to ‘food tourism’ keywords from news articles on webpage of TV and newspaper in Korea from January 1st to November 10th, 2020. From the refined data, degree centrality and eigenvector centrality were analyzed by UCINET 6. A total of 188,502 words were collected, of which the top 200 words were extracted, and 66 words were selected and analyzed through the refining process. Convergence of iterated correlations(CONCOR) showed 4 clustered named ‘core service’, ‘social environment’, ‘destinations’ and ‘COVID-19’. The “Core service” cluster contains words such as tourist, travel, tourism, food, restaurant, and the “COVID-19” group includes words such as social listing, mask, confirmed case, patient, damage, etc. In addition, the “social environment” group includes words such as online, support, investment, society, governance, and the “destinations” group includes words such as Seoul, Busan, Inchon, Gangnam, domestic and development. The spread of the COVID-19 is causing great difficulties in tourism, but it is important to prepare for a marketing strategy for food tourism in the future. Using this web information, it is expected to serve as a basis for basic data useful for establishing marketing strategies for food tourism.
