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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국조리학회 Culinary Science & Hospitality Research Culinary Science & Hospitality Research Vol.30 No.4(Wn.165)
- 발행연도
- 2024.4
- 수록면
- 71 - 86 (16page)
- DOI
- 10.20878/cshr.2024.30.4.007
이용수
DBpia Top 10%동일한 주제분류 기준으로최근 2년간 이용수 순으로 정렬했을 때
해당 논문이 위치하는 상위 비율을 의미합니다.
초록· 키워드
오류제보하기
This study aims to understand consumer perception and trends related to decaffeinated coffee through text mining text analytics), identifying key keywords connected to decaffeinated coffee. From March 14, 2019, to March 13, 2023, text documents on the network were collected, and the collected data underwent refining processes using Textom. A total of 14,204 pieces of data were collected, and after preprocessing to remove unnecessary data, a refined dataset of 7.7 MB was obtained. The collected and refined data were analyzed using natural language processing for frequency analysis, co-occurrence frequency analysis, revealing key keywords. The relationships between keywords were analyzed through connection structure and centrality analysis. Based on this, cluster analysis was conducted, identifying four core keyword clusters with structural similarity. Sentiment analysis on consumer emotions regarding decaffeinated coffee was conducted using the sentiment dictionary provided by Textom. The results of text mining analysis are as follows. Firstly, it was observed that ‘franchises’ are prominently discussed in decaffeinated-related documents. Secondly, centrality analysis for network connection structure revealed a close association between decaffeinated and coffee, followed by a strong connection to franchises. Centrality analysis was used to understand the network structure of keywords related to decaffeinated coffee, which were primarily associated with the attributes, taste, and purchase intentions of decaffeinated coffee. Thirdly, through CONCOR analysis, four key groups were identified, focusing on consumer experiences with decaffeinated coffee, health-related concerns, interest in new products, and personal transactions. Particularly, health-related keywords significantly influenced consumer concerns regarding caffeine"s adverse effects and their interest in decaffeinated coffee. Given the steady growth of the decaffeinated coffee market, the importance of utilizing these research findings for marketing strategy analysis and further research on decaffeinated coffee is evident.
목차
ABSTRACT
1. 서론
2. 문헌 연구
3. 연구 방법
4. 분석 결과
5. 결론 및 시사점
REFERENCES
참고문헌 (48)
참고문헌 신청
An, G. J. (2021). Effect of coffee shop selection attributes: Delivery app focus. Northeast Asia Tourism Research, 17(4), 213-229.
Bae, S. H., & Kim, D. J. (2021). A semantic network analysis of gastronomy tourism using social big data. Culinary Science, & Hospitality Research, 27(8), 49-59.
Bae, S. H., & Lee, S. A. (2022). A study on perception and attitude on wellness tourism using big data: Semantic network analysis and sentiment analysis. Journal of Tourism Sciences, 46(6), 149-165.
Bi, W., Zhou, J., & Row, K. H. (2011). Decaffeination of coffee bean waste by solid-liquid extraction. Korean Journal of Chemical Engineering, 28, 221-224.
Cho, Y. W., Kim S. Y., & Park, S. H. (2018). A study on the effect of consumer's attraction on the motivation of coffee consumption and preference by the types of coffee shop. International Journal of Tourism Management and Sciences, 33(8), 387-405.
Bae, S. H., & Kim, D. J. (2021). A semantic network analysis of gastronomy tourism using social big data. Culinary Science, & Hospitality Research, 27(8), 49-59.
Bae, S. H., & Lee, S. A. (2022). A study on perception and attitude on wellness tourism using big data: Semantic network analysis and sentiment analysis. Journal of Tourism Sciences, 46(6), 149-165.
Bi, W., Zhou, J., & Row, K. H. (2011). Decaffeination of coffee bean waste by solid-liquid extraction. Korean Journal of Chemical Engineering, 28, 221-224.
Cho, Y. W., Kim S. Y., & Park, S. H. (2018). A study on the effect of consumer's attraction on the motivation of coffee consumption and preference by the types of coffee shop. International Journal of Tourism Management and Sciences, 33(8), 387-405.
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