Exploiting User-Generated Content for Service Improvement: Case Airport Twitter Data

Aunimo, Lili; Martín-Domingo, Luis

doi:10.1007/978-3-031-14844-6_8

Cited by 1 publication

(2 citation statements)

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“…Ref. [46] used Twitter, where UGC was leveraged to identify possible service improvement areas. A Twitter dataset of 949,497 tweets was analysed from the four-year period from 2018 to 2021 for 100 airports-with the second half falling under the main COVID period.…”

Section: Ugc Analytical Methodsmentioning

confidence: 99%

“…The Latent Dirichlet Allocation (LDA) method was used for topic discovery and the lexicon-based method was used for sentiment analysis of the tweets. The COVID-19related tweets reported a lower sentiment by passengers, which can be an indication of the lower service level perceived [46]. Twitter and its UGC was used to analyse sourcing and verification practices on Twitter during the Brussels attacks in March 2016.…”

Section: Ugc Analytical Methodsmentioning

confidence: 99%

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Sentimental Approach to Airline Service Quality Evaluation

Badanik,

Remenysegova,

Kazda

2023

Aerospace

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This paper focuses on the analysis of traditional methods of service quality evaluation and represents a new sentimental approach to airline service quality evaluation employing user-generated content. It identifies aspects of airline service that passengers react to positively or negatively using the word cloud method—a basic straightforward exploratory analysis tool. The aim is to introduce an approach that can be implemented using freely available analytical software tools and freely available data. As a case study, authors evaluated selected airlines’ service quality using sentimental analysis of user-generated content. The research relied on sentiment analysis of Twitter posts related to selected airlines’ service quality. The paper describes how Twitter can be used for data mining, sentimental analysis, and airline service quality evaluation. The authors analysed over 30,000 posts related to the service quality of Ryanair, Southwest Airlines, American Airlines and KLM and proposed two types of word clouds (for each individual airline) which allow more informed decisions about enhancing the service quality of selected airlines. Compared to rather expensive traditional methods of airline service quality evaluation, such as onboard surveys of airline passengers or on-site surveys of passengers at airport departure gates, the key advantages of this new approach are the availability of free data and free analytical software tools. Moreover, this approach allows analysis of the service quality of competing airlines and, thus, provides internal opportunities for comparison. The results contribute to the literature by clarifying how both positive and negative passenger feedback impacts airline service quality and airline product planning.

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Section: Ugc Analytical Methodsmentioning

confidence: 99%

Section: Ugc Analytical Methodsmentioning

confidence: 99%