Abstract
This study aims to prepare an academic basis and contribute to establishing a strategic direction based on research results by examining the historical background and market conditions of coffee shops and deriving consumer perceptions by coffee shop brands using online big data. For this purpose, from January 1, 2016 to June 30, 2022, data were collected on Naver blog and Naver cafe using the keyword 'each coffee sales brand'. The collected data went through a refinement process, and word frequency analysis, TF-IDF analysis, and LDA analysis of topic modeling were performed through text mining analysis. As a result of the analysis, consumers' perceptions of each brand were derived, the implications of this were discussed, and the limitations of this study were described.
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