Browsing Faculty of Aviation and Aeronautical Science by Subject "Sentiment analysis"
Now showing items 1-5 of 5
-
Applying deep learning models to twitter data to detect airport service quality
(Elsevier, 2021-03)Measuring airport service quality (ASQ) is an important process for identifying shortages and suggesting improvements that guide management decisions. This research, introduces a general framework for measuring ASQ using ... -
An evaluation of airport service experience: An identification of service improvement opportunities based on topic modeling and sentiment analysis
(Elsevier, 2022-06)With the increase in airport alternatives and airport service variation, passengers' perception of the airport experience has changed. By working with consumer experience through customer reviews, this study aims to define ... -
Exploiting user-generated content for service improvement: Case airport twitter data
(Springer, 2022-09)The study illustrates how airport collaborative networks can profit from the richness of data, now available due to digitalization. Using a co-creation process, where the passenger generated content is leveraged to identify ... -
Social media as a resource for sentiment analysis of Airport Service Quality (ASQ)
(Elsevier, 2019-07)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 ... -
The voice of the consumer on sVoD systems during covid-19: A service opportunity mining approach
(Inst Superior Entre Douro & Vouga, 2022-01)Electronic word of mouth (e-WOM) is a vital channel for the exchange of customer-generated content. As the e-WOM messages created by consumers pile all around the Web, they generate an unbiased voice about products and ...
Share this page