Analysis of Social Issues regarding Blockchain Tourism Policy

This study aims to analyze government policies and support strategies for blockchain tourism by collecting Naver news articles and conducting frequency analysis (term frequency [TF], term frequency-inverse document frequency [TF-IDF]), latent Dirichlet allocation (LDA) topic modeling, and interpretive data modeling (IDM) to identify research questions.The results of the analysis are as follows. First, the TF for blockchain tourism policy was ranked in the order of ‘government,’ ‘blockchain,’ ‘China,’ ‘industry,’ and ‘tourism.’ The TF-IDF analysis indicated that the terms ‘game,’ ‘metaverse,’ ‘BUSAN,’ and ‘candidate’ were prominent. Second, five topics were identified: Topic 1, ‘information security’; Topic 2, ‘virtual tourism industry’; Topic 3, ‘blockchain special zone’; Topic 4, ‘global market’; and Topic 5, ‘New Deal project.’ Lastly, to examine the relative importance and similarity among the blockchain tourism policy topics, the IDM results showed relative importance values in the following order: Topic 1 (27.2%), Topic 2 (23.4%), Topic 3 (18.8%), Topic 4 (17.1%), and Topic 5 (13.6%).This study is expected to contribute to understanding the direction and goals of policies, thereby aiding in the establishment of effective blockchain tourism policies.