Sakura City Rekihaku Visitor Survey and Analysis Support Project Sakura City History Museum Visitor Survey and Analysis Support Project

Rekihaku Visitor Questionnaire Analysis Combining Quantitative and Qualitative Approaches
　E-LINE Co., Ltd. provided data-analysis support for visitor questionnaires at the National Museum of Japanese History (Rekihaku) in Sakura City. Specifically, we conducted cross-tabulation to understand visitor characteristics and usage patterns, clarifying relationships between basic attributes such as age and area of residence and factors such as purpose of visit and satisfaction ratings. This made it possible to visualize which groups visit Rekihaku and which factors are associated with satisfaction and intentions to return.

In addition, we systematically analyzed comments submitted in open-ended fields using text mining. Morphological analysis was used to extract frequently occurring words, allowing us to objectively identify exhibition content that attracted visitors' attention and service areas where improvement was requested. Because visitors' impressions and requests can be understood more deeply not only from the frequency of individual words but also from context and connections among multiple terms, combining these findings with quantitative results enabled a more multidimensional interpretation.



In addition, to present the text-analysis results visually, we created a co-occurrence network diagram. This represents relationships among words used by visitors as a network structure, making it possible to intuitively understand key terms at the center of visitors' awareness and hidden connections among concepts. As a result, interpretation of the questionnaire went beyond numerical statistics and could reflect the structure of visitors' thinking and interests. Through this analytical support, E-LINE contributed to helping the National Museum of Japanese History better understand visitor needs and use the findings to improve services and exhibition planning. By integrating quantitative and textual data, we believe we were able to provide deeper insights than conventional questionnaire analysis alone could offer.




Reference: https://www.rekihaku.ac.jp/