A Text Mining Study on the Utilization of Japanese Literary Museums as Tourism Resources ：Analyzing the Relationships between Literary Museums and Local Tourism through Reviews on “Jalan” and “4travel”

This study investigates the dynamic interconnections between Japan’s regional literary museums and nearby tourism resources, applying advanced text mining techniques to clarify how these museums function as cultural tourism assets. Primary data consists of travel reviews from “Jalan” and “4travel,” systematically extracted through Python’s Selenium package. The mecab-ipadic-neologd lexicon was employed for precise morphological segmentation, with stopwords meticulously removed to improve analytical clarity. Dirichlet-Multinomial Regression (DMR) topic modeling and Heatmap Table visualizations provide robust insights into structural relationships and visitor engagement trends associated with literary museums.Based on these findings, several key recommendations are proposed. First, the study emphasizes the importance of literary museums as core tourism assets, demonstrating how visitor experiences and semantic trends influence public perceptions of these sites as cultural landmarks and attractions. Second, it offers a framework to strengthen the synergy between literary museums and local tourism resources by mapping visitor engagement patterns, positioning these institutions as integral components within regional tourism ecosystems. Finally, this research offers critical empirical foundations for sustainable cultural tourism strategies, equipping local governments and tourism organizations with nuanced insights to optimize literary museum-centered tourism and foster enriched cultural exchanges between communities and visitors.