DOI QR코드

DOI QR Code

A Study on the Application of SNS Big Data to the Industry in the Fourth Industrial Revolution

제4차 산업혁명에서 SNS 빅데이터의 외식산업 활용 방안에 대한 연구

  • Han, Soon-lim (School of Hospitality & Tourism Management, Kyungsung University) ;
  • Kim, Tae-ho (School of Hospitality & Tourism Management, Kyungsung University) ;
  • Lee, Jong-ho (School of Hospitality & Tourism Management, Kyungsung University) ;
  • Kim, Hak-Seon (School of Hospitality & Tourism Management, Kyungsung University)
  • 한순임 (경성대학교 호텔관광외식경영학부) ;
  • 김태호 (경성대학교 호텔관광외식경영학부) ;
  • 이종호 (경성대학교 호텔관광외식경영학부) ;
  • 김학선 (경성대학교 호텔관광외식경영학부)
  • Received : 2017.09.11
  • Accepted : 2017.10.20
  • Published : 2017.10.30

Abstract

This study proposed SNS big data analysis method of food service industry in the 4th industrial revolution. This study analyzed the keyword of the fourth industrial revolution by using Google trend. Based on the data posted on the SNS from January 1, 2016 to September 5, 2017 (1 year and 8 months) utilizing the "Social Metrics". Through the social insights, the related words related to cooking were analyzed and visualized about attributes, products, hobbies and leisure. As a result of the analysis, keywords were found such as cooking, entrepreneurship, franchise, restaurant, job search, Twitter, family, friends, menu, reaction, video, etc. As a theoretical implication of this study, we proposed how to utilize big data produced from various online materials for research on restaurant business, interpret atypical data as meaningful data and suggest the basic direction of field application. In order to utilize positioning of customers of restaurant companies in the future, this study suggests more detailed and in-depth consumer sentiment as a basic resource for marketing data development through various menu development and customers' perception change. In addition, this study provides marketing implications for the foodservice industry and how to use big data for the cooking industry in preparation for the fourth industrial revolution.

Keywords

References

  1. Douglas, L. (2012). The importance of 'ig Data: A definition. Gartner, Retrieved 21 June.
  2. Food Eating Out Economy (2017). Fourth industrial revolution led by food and restaurant industry innovation.
  3. Jung, Y. C. (2012). Big data revolution and media policy issues. KISDI Premium Report, 12-02.
  4. Jung, Y. C. (2013). Data. Seoul, Communication Books.
  5. Hod L. & Melba K. (2013). The new world of 3D printing. Seoul, Hans Media.
  6. Http://www.weforum.org (2016). The fourth industrial revolution what it means and how to respond.
  7. IBM Global Business Services (2012, 10). Michael Schroeck & Rebecca Shockley & Janet Smart, Dolores Romero-Morales, Peter Tufano, Realistic Utilization of Big Data.
  8. Kim, H. S. (2017a). An exploratory study on the semantic network analysis of food tourism through the big data. Culinary Science & Hospitality Research, 23(4), 22-32. https://doi.org/10.20878/cshr.2017.23.4.003
  9. Kim, H. S. (2017b). A semantic network analysis of big data regarding food exhibition at convention center. Culinary Science & Hospitality Research, 23(3), 257-270. https://doi.org/10.20878/cshr.2017.23.3.024
  10. Korea Information Technology Agency (2016). In the era of intelligence, the big design to new Korea. IT & Future Strategy 1.
  11. Lee, B. Y., & Park, J. Y., & Yoo, J. S (2015). High-volume data processing for cloud and big data services in terms of cost savings architecture. Korea Contents Association, 15(5), 570-581.
  12. Lee, E. M. (2016). The fourth industrial revolution and changes in the industrial structure. Information and Communication Broadcasting Policy, 28(15), 1-22.
  13. Lee, J. H., & Kim, H. S. (2013). The effect of college students' confidence in nutrition knowledge on health-related behavioral intentions: The moderating effect of gender. Culinary Science & Hospitality Research, 19(4), 136-146. https://doi.org/10.20878/cshr.2013.19.5.012012012
  14. Linoff, Gordon S., & Berry, Micahel, J. A. (2011). Data mining techniques: For marketing, sales, and customer relationship management. Indianapolis, IN: Wiley.
  15. Liu, B. (2011). Web data mining. Springer.
  16. Markus H. (2011). Data mining techniques. Volume 10 May 2001, 313-355.
  17. O'eilly (2012). Big data now: Current perspectives from O'eilly readar. O'eilly Media.
  18. Samsung Economic Research Institute (2012). Bigdata; Origin of industrial crustal fluctuations. CEO Information 851.
  19. Schimon G., & Michael G. Faure (2017). Conditions for effective risk sharing against marine pollution: The case of the Ría De vigo. NHH Dept. of Business and Management Science Discussion Paper.
  20. Schwab, K. (2016). The fourth industrial revolution: What it means, how to respond.
  21. Sharon, M. (2012). Computer world blog.
  22. WEF (2016). The future of jobs, world economy forum. January 18. Davos: Switzerland Chapman.
  23. Pete et al. (2000). CRISP-DM 1.0 Step-by-step data mining guide. SPSS.
  24. World Economic Forum (2012). Big data, big impact: New possibilities for international development.

Cited by

  1. Understanding Customer Experience and Satisfaction through Airline Passengers’ Online Review vol.11, pp.15, 2017, https://doi.org/10.3390/su11154066