DOI QR코드

DOI QR Code

A Semantic Network Analysis of Big Data regarding Food Exhibition at Convention Center

전시컨벤션센터 식품박람회와 관련된 빅데이터의 의미연결망 분석

  • Kim, Hak-Seon (Dept, of Foodservice Management, Kyungsung University)
  • 김학선 (경성대학교 호텔관광외식경영학과)
  • Received : 2017.04.06
  • Accepted : 2017.04.21
  • Published : 2017.04.30

Abstract

The purpose of this study was to visualize the semantic network with big data related to food exhibition at convention center. For this, this study collected data containing 'coex food exhibition/bexco food exhibition' keywords from web pages and news on Google during one year from January 1 to December 31, 2016. Data were collected by using TEXTOM, a data collecting and processing program. From those data, degree centrality, closeness centrality, betweenness centrality and eigenvector centrality were analyzed by utilizing packaged NetDraw along with UCINET 6. The result showed that the web visibility of hospitality and destinations was high. In addition, the web visibility was also high for convention center programs, such as festival, exhibition, k-pop and event; hospitality related words, such as tourists, service, hotel, cruise, cuisine, travel. Convergence of iterated correlations showed 4 clustered named "Coex", "Bexco", "Nations" and "Hospitality". It is expected that this diagnosis on food exhibition at convention center according to changes in domestic environment by using these web information will be a foundation of baseline data useful for establishing convention marketing strategies.

Keywords

References

  1. Buhalis, D. (2000). Marketing the competitive destination of the future. Tourism Management, 21(1), 97-116. https://doi.org/10.1016/S0261-5177(99)00095-3
  2. Choi, H., Kwak, G., & Kim, H. (2017). A positioning study of national food: In perspective of Korean, American, Chinese food tourists. Culinary Science & Hospitality Research, 23(2), 86-94. https://doi.org/10.20878/cshr.2017.23.2.009009009
  3. Deery, M., & Jago, L. (2010). Social impacts of events and the role of anti-social behaviour. International Journal of Event and Festival Management, 1(1), 8-28. https://doi.org/10.1108/17852951011029289
  4. Freeman III, A. M. (1979). Benefits of environmental improvement: Theory and practice. Johns Hopkins University Press, Baltimore, MD.
  5. Freeman, L. C., Roeder, D., & Mulholland, R. R. (1979). Centrality in social networks: II. experimental results. Social Networks, 2(2), 119-141. https://doi.org/10.1016/0378-8733(79)90002-9
  6. He, W., & Xu, G. (2016). Social media analytics: Unveiling the value, impact and implications of social media analytics for the management and use of online information. Online Information Review, 40(1).
  7. Jang, M., & Yoon, Y. (2016). Research into changes in government policies and public perceptions on camping via analyses of big data from social media. Korean Journal of Tourism Research, 31, 91-112.
  8. Jeon, H. (2014). VIP report for sustainable growth: MICE industry competitiveness in Korea and implications. Hyundai Research Institute VIP Report, 561(0), 1-23.
  9. Joung, H. D., Choi, E. K. C., Ahn, J., & Kim, H. (2014). Healthy food awareness, behavioral intention, and actual behavior toward healthy foods: Generation Y consumers at university foodservice. Journal of the Korean Society of Food Culture, 29(4), 336-341. https://doi.org/10.7318/KJFC/2014.29.4.336
  10. Jung, S., & Lee, J. (2016). The creation and transformation of knowledge in convention and exhibition industry. Journal of MICE & Tourism Research, 46(0), 43-57.
  11. Kim, C. W., & Heo, J. (2011). Korea tourism history research articles: Historical review on Korean convention industry. Journal of Tourism Sciences, 35(10), 517-533.
  12. Kim, H., Joung, H., & Choi, E. (2016). A study of nutrition knowledge, confidence, and body image of university students. Culinary Science & Hospitality Research, 22(1), 70- 77. https://doi.org/10.20878/cshr.2016.22.1.008008008
  13. Kim, S., Park, S., Sun, M., & Lee, J. (2016). A study of smart beacon-based meeting, incentive trip, convention, exhibition and event (MICE) services using big data. Procedia Computer Science, 91, 761-768. https://doi.org/10.1016/j.procs.2016.07.072
  14. Kim, H., Lee, K., Lee, D., Joung, H., & Yuan, J. J. (2012). Assessing the quality of A restaurant's website using DINEWEBQUAL. Journal of Quality Assurance in Hospitality & Tourism, 13(3), 235-245. https://doi.org/10.1080/1528008X.2012.692278
  15. Kim, H., Oh, C., & No, J. (2016). Can nutrition label recognition or usage affect nutrition intake according to age? Nutrition, 32(1), 56-60. https://doi.org/10.1016/j.nut.2015.07.004
  16. Lee, H., & Yoon, Y. (2011). The impact of convention destination image on intention to recommend: The moderating effect of convention destination personality. Journal of Tourism Sciences, 35(3), 225-241.
  17. Lee, K. E. (2016). An examination of the decision-making process for utilization of mobile applications in the MICE industry.
  18. Lee, S., & Jeon, I. (2016). The study on the effect of environmental sustainability on the competitiveness and business performance of stakeholders in MICE industry. Journal of Tourism & Leisure Research, 28(6), 177-196.
  19. Lee, S., Lee, K., Kwak, G., & Kim, H. (2017). The effect of the Korean wave on Malaysian university students' perception. Culinary Science & Hospitality Research, 23(1), 79-83. https://doi.org/10.20878/cshr.2017.23.1.009009009
  20. Lee, S., Siong, K., Lee, K., & Kim, H. (2016). Non-muslim customers' purchase intention on halal food products in malaysia. Culinary Science & Hospitality Research, 22(1), 108-116. https://doi.org/10.20878/cshr.2016.22.1.012012012
  21. Martin, J. C., Roman, C., & Gonzaga, C. (2017). Quality of service and segmentation in the MICE industry: An approximation based on fuzzy logic. Journal of Convention & Event Tourism, 18(1) 1-25. https://doi.org/10.1080/15470148.2016.1154808
  22. Ministry of Culture, Sports and Tourism. (2016). Korea ranks second in the world in 2015 (asia's first): Construction and operation of the ministry of education, culture, sports, science and technology. Retrieved from http://www.mcst.go.kr/web/s_notice/press/pressView.jsp?pSeq=15347
  23. Oh, I., Lee, T., & Chon, C. (2015). A study on awareness of korea tourism through big data analysis. Journal of Tourism Sciences, 39(10), 107-126.
  24. Park, S. (2009). Semantic network analysis of presidential debates in 2007 election in Korea. Korean Journal of Communication & Information, 45, 220-254.
  25. Phillips, P., Barnes, S., Zigan, K., & Schegg, R. (2016). Understanding the impact of online reviews on hotel performance: An empirical analysis. Journal of Travel Research, 0047287516636481 https://doi.org/10.1177/0047287516636481
  26. Shi, M., Zhu, W., Yang, H., & Li, C. (2016). Applying semantic web and big data techniques to construct a balance model referring to stakeholders of tourism intangible cultural heritage. International Journal of Computer Applications in Technology, 54(3), 192-200. https://doi.org/10.1504/IJCAT.2016.079873
  27. Shim, H., Kim, Y., Shon, H., & Lim, J. (2011). An exploratory usage pattern research of smartphone and social media users through semantic network analysis : Gender and age differences in perception and evaluation of usage pattern. Korean Journal of Broadcasting and Telecommunication Studies, 25(4), 82-138.
  28. Son, J., Lee, E., & Kim, H. (2016). Perceived value, importance of nutrition information, and behavioral intention for food tourism in Busan. Culinary Science & Hospitality Research, 22(1), 135-140. https://doi.org/10.20878/cshr.2016.22.8.012012012
  29. Song, S., & Kim, D. (2014). Study on correlation between the satisfaction of the convention participants and their expenditures. Journal of Tourism & Leisure Research, 26 (3), 283-299.
  30. Torri, L., & Salini, S. (2016). An itinerant sensory approach to investigate consumers' perception and acceptability at a food exhibition. Food Research International, 90, 91-99. https://doi.org/10.1016/j.foodres.2016.10.041
  31. Yoo, S. (2011). The effect of urban tourism satisfaction on revisit and word-of-mouth. Journal of Hospitality and Tourism Studies, 13(1), 53-72.
  32. Yoon, S., Ha, J., & Oh, S. (2012). Analysis of the effect relationship among brand relationship quality, satisfaction, trust, loyalty, and familiarity of tourism destination. The Academy of Customer Satisfaction Management, 14(2), 41- 60.
  33. Zhang, L., Qu, H., & Ma, J. (2010). Examining the relationship of exhibition attendees' satisfaction and expenditure: The case of two major exhibitions in China. Journal of Convention & Event Tourism, 11(2) 100-118. https://doi.org/10.1080/15470141003794972

Cited by

  1. 빅데이터를 활용한 음식관광관련 의미연결망 분석의 탐색적 적용 vol.23, pp.4, 2017, https://doi.org/10.20878/cshr.2017.23.4.003
  2. A Study of Comparison between Cruise Tours in China and U.S.A through Big Data Analytics vol.23, pp.6, 2017, https://doi.org/10.20878/cshr.2017.23.6.001
  3. 제4차 산업혁명에서 SNS 빅데이터의 외식산업 활용 방안에 대한 연구 vol.23, pp.7, 2017, https://doi.org/10.20878/cshr.2017.23.7.001
  4. Trend Analysis of Grow-Your-Own Using Social Network Analysis: Focusing on Hashtags on Instagram vol.24, pp.5, 2017, https://doi.org/10.11628/ksppe.2021.24.5.451