Analysis of Text Data on "Drip Coffee" Using Social Big Data
Minseok Kim, Dong-Jin Kim · Culinary Science & Hospitality Research · 2023
This study was conducted to understand the meaning of text data held by "drip coffee" using social big data and to contribute the derived keywords to the establishment and utilization of marketing strategies in the coffee market. The study period was set to one year from January 1, 2022 to December 31, 2022, and data on "Drip Coffee" were collected by selecting Naver, Daum, and Google. As a result of the collection, a total of 22,164 posts were collected, and a total of 36,874 words were extracted as a result of text mining. The analysis was conducted after a purification process before the analysis, and the summary of the analysis results is as follows. Drip Coffee, which was No. 1 in TF, fell to No. 10 in TF-IDF. It can be seen that the frequency of appearance is high through a refining process that unifies words, while various meanings of No. 1 in TF-IDF played an important role in the document, As a result of CONCOR analysis, a total of five clusters were formed. As the coffee market continues to develop and changes in various forms, academia and industry should conduct alternatives and steady research on changing trends through periodic monitoring. As a limitation of this study, there was a limitation to the data as the study was conducted with only text data, and it was difficult to grasp the coffee market macroscopically because only "drip coffee" in the coffee market was selected. Therefore, in subsequent studies, research using various data other than text data is needed, and finally, research on various topics other than drip coffee is considered necessary.