2024 Volume 12 Issue 1 Article ID: 23-00186
Recently, foreign tourists traveling to Japan are pursuing self-likeness, self-worth, and diversified travel experiences as tourism needs have become increasingly personalized for visitors. In this study, we used the Latent Dirichlet Allocation model and Word2vec model of natural language processing to analyze the web travel notes posted on the Chinese visitor website Mafengwo written by Chinese tourists who visited Japan. Using the analytical results, we identified the tourism themes and the visit patterns of the Chinese tourists travelling to Japan and how they have changed. Furthermore, we also identified impressive and attractive local and regional tourism resources in some regions in Japan. Based on the analytical results, the policy to promote inbound tourism industry in local regions was also discussed.
