Social media as a resource for sentiment analysis of Airport Service Quality (ASQ)

• Published in: Journal of air transport management Vol. 78; pp. 106 - 115
• Main Authors: Martin-Domingo, Luis, Martín, Juan Carlos, Mandsberg, Glen
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2019
• Subjects: Airport; Quality; Sentiment Analysis; Service; Twitter; Service; Twitter; Sentiment Analysis; Quality; Airport
• ISSN: 0969-6997; 1873-2089
• DOI: 10.1016/j.jairtraman.2019.01.004

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. •Twitter content can complement more traditional research methods such as surveys.•Text mining and sentiment analysis serve to analyse airport service quality (ASQ).•Heathrow airport provides good WiFi, WCs, food & beverage and lounge services.•Waiting, parking, immigration, staff and passport control need improvement.•Ground transport and wait times are the most cited airport service attributes.