Impact of emotional design elements on consumption value derived by text mining on NAVER Smart Place cafe reviews

This paper conducted an in-depth analysis of Naver Smart Place Cafe review data to explore the relationship between emotional design elements and consumer value. Using text mining techniques, we derived the core elements of emotional design and types of consumer value from 54,437 reviews collected from July 2024 to June 2025. Our emotional analysis revealed that 94.12% of all reviews had positive connotations. Through latent Dirichlet allocation (LDA) topic modeling and keyword analysis, four main themes aligning with the instinctive, behavioral, and reflective dimensions, as well as the functional, emotional, social, and exploratory consumer value structures were identified. Additionally, sentiment word frequency analysis showed that positive words such as “delicious,” “sweet,” “pleasant,” and “satisfying” appeared frequently. This suggests that emotional design elements play an important role in shaping consumers' emotional responses and positive experiences. Unlike previous survey-based research methods, this paper used unstructured text data generated by consumers, overcoming methodological limitations in quantitatively assessing consumers' natural and intuitive emotional responses. Future research should quantitatively validate these findings using structural equation modeling and expand the scope to various platforms. The findings of this paper are expected to provide practical insights to assist café operators and space designers in developing emotional design strategies and improving customer experiences.