Research on post occupancy evaluation of Oze National Park in Japan based on online reviews

Abstract

With the development of internet, online reviews are user-generated content posted in the web-media era and can extract meaning from the comments through data-mining technology. The study uses python crawler to collect reviews and conduct post-occupancy evaluation on Oze National Park (ONP), a natural conservation in Japan. Content and semantic network analysis were adopted to study the high-frequency words and their relationships. Latent Dirichlet Allocation was utilized to uncover the dimensions of the comments. The conclusions were as follows: 1) Japanese tourists focused on landscape plants and nature, while the Chinese focused on facilities and experience, English concentrated on hiking activity. 2) The Ozegahara Plateau route and the Lake Ozenuma route were the two main courses in ONP. 3) 48% of the concept of the landscape of ONP was conveyed to the users. 4) Male tourists focused on location information and landscape, while females were concerned about the process and experience. The single-visitors paid attention to the road and boardwalk. Family tourism concentrated on experience and time while friends and couple-visitors preferred to perceive action. 5) The Lysichiton Americanus had become a basic feature of ONP, and visitors were satisfied with the landscape and experience.

Keywords

• oze national park
• online reviews
• perception
• big data
• python