Airline Customer Satisfaction Analysis using Social Media Sentiment Evaluation: Full Service Carriers vs. Low Cost Carriers

소셜 미디어 감성평가를 활용한 항공사 고객만족도 분석 - 대형항공사와 저비용항공사 비교연구

  • Lee, Ju-Yang (Division of Tourism, Baekseok Culture University) ;
  • Jang, Phil-Sik (Dept. of Information & Logistics, Sehan University)
  • 이주양 (백석문화대학교 관광학부) ;
  • 장필식 (세한대학교 정보물류학과)
  • Received : 2017.05.03
  • Accepted : 2017.06.20
  • Published : 2017.06.28


This study investigates customer satisfaction with full service carriers (FSC) and low cost carriers (LCC) using social media sentiment evaluation. From 2008 to 2016, a total of 77,591 tweets about two FSC and six LCC were aggregated and classified as per airline choice factors. Sentiment evaluation was employed to assess customer satisfaction by three appraisers. The results showed that customer satisfaction with LCC was significantly higher (p<0.001) compared to FSC. Furthermore, overall customer satisfaction with both FSC and LCC has been facing a consistent downward trend since the last seven years. The results also highlighted low customer satisfaction with respect to booking and flight operation factors, and a steep decline in customer satisfaction across booking, onboard services, and marketing factors for FSC. The results of this study have practical implications for the airline industry, which can use this quantitative data to improve customer satisfaction with FSC and LCC.


Supported by : 세한대학교


  1. J. Y. Lee, "The Effect of the Satisfaction with major on Career Exploration Behavior of the Students in the department of Airline Service: Focused on the comparison between 2year and 4year colleges", Journal of the Korea Convergence Society Vol. 8. No. 4, pp. 207-218, 2017.
  2. Ministry of Land, Infrastructure and Transport, Aviation Market Trend & Analysis, Vol. 57, 2017.
  3. W. J. Lee, The influence on the customer satisfaction and the reuse intentions of selection factors on Incheon-North America route, Hanseo University, Master's thesis, 2014.
  4. J. Y. Lee, P. S. Jang, "Study on Research Trends in Airline Industry using Keyword Network Analysis: Focused on the Journal Articles in Scopus", Journal of the Korea Convergence Society Vol. 8. No. 5, pp. 169-178, 2017.
  5. S. B. Kim, J. W. Park, "A Study on the Relative Importance of Airline Choice Factors -Concentrating on the Differences by Types of Airlines-", Journal of the Aviation Management Society of Korea, Vol. 13. No. 1, pp. 45-61, 2015.
  6. G. S. Kim, J. E. Jo, "The Relationships of Importance-Performance and Satisfaction on Airline Service Quality", Korean Journal of Tourism Research, Vol. 19. No. 2, pp. 35-61, 2004.
  7. S. M. Oh, S. H. Ko, "Research on Airline Selection Attributes by IPA among Foreign Tourists Visiting Korea", The Korea Contents Association, Vol. 14. No. 1, pp. 466-477, 2014.
  8. J. G. Lee, G. S. Yoo, "A Study on Positioning through choice attributes of Airline", Journal of Tourism Management Research, Vol. 11. No. 4, pp. 27-51, 2007.
  9. J. S. Ryu, Y. O. Park, "Importance-Performance Analysis of Selection Attribute Assessment for Airline - A Case of Domestic Airlines -", International Journal of Tourism and Hospitality Research, Vol. 20. No. 2, pp. 157-171, 2006.
  10. Y. S. Park, "Study on The Airline Service Consumer's Choice Attributes of An Airlines Using AHP", Journal of Tourism and Leisure Research, Vol. 25. No. 8, pp. 409-424, 2013.
  11. S. H. Han, The importance research of airline choice attributes of Korean travelers bounding for Southeast Asia: Focusing on comparison low cost carrier with full service carrier, Jeju National University, Master's thesis, 2015.
  12. J. Y. Lee, P. S. Jang, "Effects of message polarity and type on word of mouth through SNS (Social Network Service)", The Journal of Digital Policy & Management, Vol. 11, No. 6, pp. 129-135, 2013.
  13. P. S. Jang, "Study on principal sentiment analysis of social data", Journal of The Korea Society of Computer and Information, Vol. 19, No. 12, pp.49-56, 2014.
  14. Statista Inc., "Number of monthly active Twitter users worldwide from 1st quarter 2010 to 1st quarter 2017 (in millions)", (April 30, 2017).
  15. Twitter, Inc., "The Streaming APIs Overview",
  16. H. H. Kim, P. S. Jang, "Differences in Sentiment on SNS : Comparison among Six Languages", Journal of Digital Convergence Vol 14, No. 3, pp. 165-170, 2016.
  17. P. S. Jang, "Self-Disclosure and Boundary Impermeability among Languages of Twitter Users", Journal of the Korea Contents Association, Vol. 16, No. 4, pp. 434-441, 2016.
  18. S. H. Lee, K. S. Kim, "Influences of Entertainment Programs on the Formation of Public Opinion in Twitter", Journal of digital Convergence , Vol. 13, No. 4, pp. 329-340, 2015.
  19. Y. S. Yoo, B. Y. Sohn, "Music Listening Behavior analysis of Twitter User and A Comparative Study of Domestic Music Rank", Journal of digital Convergence , Vol. 14, No. 5, pp. 309-316, 2016.
  20. M. Choi, "An Efficient Method for Design and Implementation of Tweet Analysis System", Journal of digital Convergence , Vol. 13, No. 2, pp. 43-50, 2015.
  21. Su Hyeon Namn, Kyoo-Sung Noh, "A Study on the Effective Approaches to Big Data Planning", Journal of digital Convergence , Vol. 13, No. 1, pp.227-235, 2015.
  22. J. Harrison, & M. J. Harrison, "Package RSelenium",
  23. S. H. Hong, "New Authentication Methods based on Users Behavior Big Data Analysis on Cloud," Journal of IT Convergence Society for SMB, Vol. 6, No. 4, pp. 31-36, 2016.
  24. Y. S. Jeong, "Business Process Model for Efficient SMB using Big Data," Journal of IT Convergence Society for SMB, Vol. 5, No. 4, pp. 11-16, 2015.