This study investigated main factors for activating local tourism of Jeollabuk-do with big data analysis. We gathered tourism big data from public open data sources and social network services(SNS) and used the analysis tools,‘Opinion Mining’,...

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
다국어 초록 (Multilingual Abstract)
This study investigated main factors for activating local tourism of Jeollabuk-do with big data analysis. We gathered tourism big data from public open data sources and social network services(SNS) and used the analysis tools,‘Opinion Mining’,...
This study investigated main factors for activating local tourism of Jeollabuk-do with big data analysis. We gathered tourism big data from public open data sources and social network services(SNS) and used the analysis tools,‘Opinion Mining’,‘Text Mining’and ‘Social Network Analysis(SNA)’. The opinion mining and text mining analysis identified the key local contents of the 14 areas of Jeollabuk-do and the evaluations of customers on local tourism. The social network analysis detected the relations between their contents and figured the importance of contents. The results of this research showed that each locations in Jeollabuk-do had their specific contents attracting visitors and the number of the contents affected the scale of tourists. Also, when their tourism contents were highly correlated with the another contents, a number of visitors might be large. Hence strong connections among their contents are the point to activate local tourism. The social network analysis divided the contents into several clusters and derived the eigenvector centralities of the content nodes implying the role importance of them in the network. We found out that the tourism were active when the nodes at high value of the eigenvector centrality were evenly distributed in every clusters, however the results were contrary when the nodes were located in a few clusters. This study suggested an action plan to extend local tourism that develop valuable contents and connect the content clusters properly.
Key Word: local tourism, big data, a plan for activation
목차 (Table of Contents)