A Study on the perception of coffee shop brands using big data

Min-sik Myeong, Sang-hee Cho
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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.
基于大数据的咖啡店品牌感知研究
本研究旨在通过考察咖啡店的历史背景和市场状况,利用网络大数据得出咖啡店品牌的消费者认知,为研究成果奠定学术基础,并为建立战略方向做出贡献。为此,从2016年1月1日到2022年6月30日,使用关键词“每个咖啡销售品牌”在Naver博客和Naver cafe收集数据。对收集到的数据进行细化处理,通过文本挖掘分析进行词频分析、TF-IDF分析和主题建模的LDA分析。作为分析的结果,消费者对每个品牌的看法得到了推导,讨论了这一影响,并描述了本研究的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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