중국 개별 관광객의 서울 지역 다(多) 목적지 관광행동 연구 : 데이터 마이닝과 소셜 네트워크 분석을 중심으로

This paper analyzed the online review data of Chinese independent travelers visiting Seoul available on the post travel review community site mafengwo.cn. Through the social network analysis, we constructed structured patterns of tourist places visited by tourists and identified dynamic the relationship between multi-destination tourist behavior and tourist destinations. The results are as follows. Firstly, the high density value of 0.2261 (22.61 %) obtained by density analysis showed that the most connections between tour destination nodes are organic. Secondly, the ranks of tourist places according to the centralities of inward connection degree and outward connection degree are proved to be different from each other. Thirdly, the media-centric analysis articulated the highly interconnected tourist sites. These results provide useful information about independent tourists’ behaviors and visiting patterns as well as the roles of each tour destination site. The results could help practitioners and public officers to develop better tour packages and to better promote tourism in Seoul. In addition, this study introduced a data mining method overcoming the traditional survey drawbacks of limited budget and time. In other words, by using extracted from the contents of a website voluntarily written by tourists. It is advantageous that the cost and time required for collecting data are relatively small and can be studied using a large amount of data. Furthermore it is expected that future research investigating the differences of visiting places in terms of diverse cities, years, seasons, and travel purposes will use the big data analysis method presented in this study.