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Analyzing passengers’ emotions following flight delays- a 2011–2019 case study on SKYTRAX comments

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  • Song, Cen
  • Guo, Jingquan
  • Zhuang, Jun

Abstract

The text mining technology enables researchers or enterprises to automatically and efficiently access the information in text comments. This paper obtains 24,165 reviews from SKYTRAX between September 2011 and March 2019, 5700 of which express that passengers had experienced flight delays. It uses sentiment analysis based on a sentiment dictionary to classify user reviews and uses co-occurrence analysis to identify passengers' concerns on different aspects of service in the aviation industry. The results of the user sentiment analysis show that there is a significant and negative correlation between the user's emotions and their flight delay experiences. After flight delay, passengers' attention to the service aspects has increased, while satisfaction with the airport service has dropped dramatically. This paper shed some new light on public opinion about flight delays.

Suggested Citation

  • Song, Cen & Guo, Jingquan & Zhuang, Jun, 2020. "Analyzing passengers’ emotions following flight delays- a 2011–2019 case study on SKYTRAX comments," Journal of Air Transport Management, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:jaitra:v:89:y:2020:i:c:s0969699720304877
    DOI: 10.1016/j.jairtraman.2020.101903
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    References listed on IDEAS

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    1. Fang, Bin & Ye, Qiang & Kucukusta, Deniz & Law, Rob, 2016. "Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics," Tourism Management, Elsevier, vol. 52(C), pages 498-506.
    2. Kim, Kun & Park, Oun-joung & Yun, Seunghyun & Yun, Haejung, 2017. "What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 362-369.
    3. Sternberg, Alice & Carvalho, Diego & Murta, Leonardo & Soares, Jorge & Ogasawara, Eduardo, 2016. "An analysis of Brazilian flight delays based on frequent patterns," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 282-298.
    4. Kim, Nam-Yi & Park, Jin-Woo, 2016. "A study on the impact of airline service delays on emotional reactions and customer behavior," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 19-25.
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    Cited by:

    1. Cen Song & Sijia Zhou & Kyle Hunt & Jun Zhuang, 2022. "Comprehensive Evolution Analysis of Public Perceptions Related to Pediatric Care: A Sina Weibo Case Study (2013–2020)," SAGE Open, , vol. 12(1), pages 21582440221, March.
    2. Pereira, Francisco & Costa, Joana Martinho & Ramos, Ricardo & Raimundo, António, 2023. "The impact of the COVID-19 pandemic on airlines’ passenger satisfaction," Journal of Air Transport Management, Elsevier, vol. 112(C).
    3. Bakır, Mahmut & Özdemir, Emircan & Akan, Şahap & Atalık, Özlem, 2022. "A bibliometric analysis of airport service quality," Journal of Air Transport Management, Elsevier, vol. 104(C).

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