Proposal for a system for extracting points for improvement in tourist attractions using word-of-mouth data posted on travel information websites.

Abstract

In Japan, the declining population, falling birthrate, and aging population in rural areas are posing the challenge of how to maintain and revitalize the functions of local communities. In order to develop the tourism industry, it is necessary to understand the points to be improved in tourist attractions as perceived by tourists, and to plan and implement new measures accordingly. This study collects word-of-mouth data on tourist spots from travel information websites, which are among the big tourist data accumulated by the spread of the Internet in recent years, and extracts sentiments that suggest negative feelings of touristsfrom the word-of-mouth data by performing sentiment analysis using deep learning. Based on the evaluations obtained through interviews with tourism researchers, we discussed the significance of the system and points to be improved.