Supervisor
Dr. Muhammad Iqbal
Programme
BSc (Hons) in Computing in IT
Subject
Computer Science
Abstract
PXAA (Passenger Experience Analytics Assistant) is a machine learning and decision-support prototype developed to analyse airline passenger complaints using sentiment analysis and complaint classification techniques. The project follows the CRISP-DM methodology and uses airline passenger reviews collected from AirlineQuality.com through Python web scraping. Natural language processing (NLP) techniques were applied to clean and preprocess the textual data, while logistic Regression was used to classify passenger sentiment into positive, negative and neutral categories.
The project also implemented rule-based complaint classification to identify common complaint themes such as delays, baggage issues, customer service problems, comfort issues, payments/refund complaints and communication failures. These complaint categories were mapped to possible root-cause categories to support airline management decision-making.
The final model achieved strong performance after dataset balancing, with an overall accuracy of 81% and significant improvement in neutral sentiment classification. PXAA demonstrates how unstructured passenger reviews can be transformed into structured business insight that supports airline service improvement and operational investigation.
Date of Award
2026
Full Publication Date
2026
Access Rights
open access
Document Type
Undergraduate Project
Resource Type
bachelor thesis
Recommended Citation
Acacio da Silva, A., & Rabelo de Campos Nunes, S.
(2026) PXAA: A Root-Cause Decision-Support System for Airline Passenger Complaints Using Sentiment Analysis and Complaint Classification CCT College Dublin.
DOI: https://doi.org/10.63227/652.299.148