Author
Martin-Domingo, Luis
Publication Date
2019-07
Publication Place
-
Elsevier
Subject
Airport, Service, Quality, Twitter, Sentiment analysis
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
0969-6997
Record ID
e830f172-8911-4b03-9c9a-7a28618841f7
Library Location
Aviation Management
Date
2019-07
Sample Text
User generated content (UGC) is providing new broad information datasets about airport service quality (ASQ) that are more easily available to researchers than information gathered using traditional techniques, such as surveys conducted with passengers. Research in the field is characterized by UGC provided on specialized blogs and websites. This study utilizes London Heathrow airport's Twitter account dataset and applies the sentiment analysis (SA) technique to measure ASQ. The aim of this research is to explore how SA techniques can identify new insights beyond those provided by more traditional methods. The dataset includes 4392 tweets and the SA identifies 23 attributes that can be used for comparison with other ASQ scales. Findings indicate that the frequency of passenger references to the attributes of the scale differs significantly in some cases and that the discernment of these differences can provide actionable insights for airport management when improving airport service quality.
DOI
10.1016/j.jairtraman.2019.01.004
Cilt
78
