In the modern foodservice industry, SNS has become a key marketing channel shaping consumer perceptions through user-generated content and advertising. Yet the rapid growth of food-related ads raises concerns over false and exaggerated claims, requiring objective analysis of consumer awareness. This study analyzes perceptions of misleading SNS foodservice advertising using big data collected with the keyword set “SNS + foodservice + advertisement.” Keyword network and CONCOR analysis revealed semantic clusters of advertising-related terms, while sentiment analysis showed that 83% of responses were positive (“good feeling,” “interest,” “joy”) and 17% were negative (“disgust,” “anger,” “fear”), reflecting both engagement and distrust. The findings indicate that SNS foodservice advertising should move beyond simple information delivery to ensure consistency between consumer experience and brand communication. Unlike prior qualitative approaches, this study provides an empirical perspective by integrating data-driven structural and emotional analysis. Future research should compare different platforms and refine sentiment methods, while policy measures are needed to strengthen transparency and accountability in SNS advertising.
목차
Abstract 1. Introduction 2. Research Background 2.1 Big Data 2.2 SNS Foodservice Advertising 2.3 False and Exaggerated Advertising 3. Research Method 3.1 Research Target and Scope 3.2 Analysis Method 4. Analysis Result 5. Conclusion References
키워드
big dataSNSadvertisingfalse and exaggeration advertising.
저자
Jin Zhen [ Ph. D. student, Department of Immersive Content Convergence, Graduate School, Kwangwoon University, Seoul, Korea ]
Gi-Hwan Ryu [ Professor, Department of Tourism and Food Industry, Graduate School of Smart Convergence, Kwangwoon University, Seoul, Korea ]
Dong-Yeon Lee [ ***Master D. Student, Department of Tourism and Food Industry, Graduate School of Smart Convergence, Kwangwoon University, Seoul, Korea ]
Corresponding Author