earticle

영어

This study utilized big data to understand consumers' perceptions of bakery cafes, which have become a post-COVID-19 consumer trend This study utilized big data to understand consumers' perceptions of bakery cafes, which have become a post-COVID-19 consumer trend. By doing so, aimed to use it as a basis for understanding the meaning of consumer behavior using bakery cafes. To do so, we collected titles and original posts containing the word "bakery cafe" from web pages, blogs, and cafes on Naver, Daum, Google, and Twitter from January 1, 2020 to July 4, 2023. Through the Textom and UCINET 6.0 to frequency analysis, identify structural characteristics of the network, key word centrality analysis, and CONCOR(CONvergence of iterated CORrelation) analysis. The results of this study are as follows: First, The top 10 words with the highest frequency of appearance are ‘bakery cafe’, ‘cafe', ‘bakery', ‘bakeies', ‘big store', ‘recommended', ‘matzip', ‘coffee', ‘variety', ‘varieties'. Second, The degree centrality analysis results show that the top 10 words are ‘bakery cafe’, ‘cafe', ‘bakery', ‘big store', ‘recommended', ‘matzip', ‘coffee', ‘variety', ‘varieties', ‘dessert’. So overall, higher frequency and higher importance words indicate that they are more central to the connection. Through a CONCOR analysis, keywords were divided into three clusters. Each cluster was named as ' bakery cafe image, 'bakery cafe usage status', and 'bakery cafe selection properties'. And specially, Each cluster contains a neighborhood associated with a bakery cafe. Therefore, it is necessary to establish a marketing strategy for bakery cafes based on the results of this study.