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

Cen Song, Jingquan Guo and Jun Zhuang ()

Journal of Air Transport Management, 2020, vol. 89, issue C

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.

Keywords: Flight delay; Sentiment analysis; Text mining (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:89:y:2020:i:c:s0969699720304877

DOI: 10.1016/j.jairtraman.2020.101903

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