Abstract
The purpose of this study is to analyze the contemporary trend and relationship structure of domestic travel related to travel week. For this purpose, this study selected Instragram hashtag, one of the most popular SNS these days, and use Word2Vec (word embedding to vector) as a new word embedding method for big data analysis, cluster analysis, and social network analysis for centrality analysis including degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality of travel week’s keywords. The main results of this study show that family travel, travel in fall season and Kangwon province and Busan city as destinations of travel week have high centrality and influence. These results will be a useful guideline for policy makers, marketing managers and tourism planners of DMO in sustaining and expanding travel week policy.
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