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

Name: Social media as a resource for sentiment analysis of Airport Service Quality (ASQ)
Author: Martin-Domingo, Luis

İsim	Social media as a resource for sentiment analysis of Airport Service Quality (ASQ)
Yazar	Martin-Domingo, Luis
Basım Tarihi:	2019-07
Basım Yeri	- Elsevier
Konu	Airport, Service, Quality, Twitter, Sentiment analysis
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0969-6997
Kayıt Numarası	e830f172-8911-4b03-9c9a-7a28618841f7
Lokasyon	Aviation Management
Tarih	2019-07
Örnek Metin	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

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

Yazar Martin-Domingo, Luis

Basım Tarihi 2019-07

Basım Yeri - Elsevier

Konu Airport, Service, Quality, Twitter, Sentiment analysis

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0969-6997

Kayıt Numarası e830f172-8911-4b03-9c9a-7a28618841f7

Lokasyon Aviation Management

Tarih 2019-07

Örnek Metin 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