Okanagan sentiment analysis of airlines reviews
department or school: Science, Irving K. Barber Faculty of (Okanagan)
department or school: Computer Science, Mathematics, Physics and Statistics, Department of (Okanagan)
data provider: DSpace
degree campus: UBCO
creator: Sim, Hong-Jiang
issued: 2023-01-19T18:27:19Z
issued: 2023
related degree: Master of Science - MSc
degree grantor: University of British Columbia
description: The COVID-19 pandemic has wreaked financial devastation for airlines. As travel restrictions eases, it is important for airlines to gather and assess the opinions of passengers in order to meet new expectations. With the availability of online electronic platforms, it has become feasible to collect customer reviews on a large scale. Collecting, processing and deciphering textual data remain a challenge to most. This thesis details the collection of textual review data from SkyTrax and Trip Advisor. Subsequently, it demonstrates the use of quantitative sentiment scoring of the textual reviews, exploratory data analysis and statistical modelling to ascertain factors that affect passenger perceptions of airlines services. Specifically, we developed a linear mixed model with passengers and airline as random to rank various airlines with respect to sentiment scores, while confirming fixed factors which affect these scores. The application of this model allows for interpretability to the expectations and recommendations made by various passengers of airlines, measures the performance of airlines with respect to customer experience.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/83687
note: Sentiment Analysis of AirlinesReviewsbyHong-Jiang SimB.Sc., Simon Fraser University, 2015A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF SCIENCEinThe College of Graduate Studies(Computer Science)THE UNIVERSITY OF BRITISH COLUMBIA(Okanagan)January 2023© Hong-Jiang Sim 2023The following individuals certify that they have read, and recommend tothe College of Graduate Studies for acceptance, a thesis/dissertation titled:SENTIMENT ANALYSIS OF AIRLINE REVIEWSsubmitted by HONG-JIANG SIM in partial fulfillment of the requirementsof the degree of Master of Science.Examining Committee:Dr. Paramjit Gill, Irving K. Barber Faculty of ScienceSupervisorDr. Fatemeh Fard, Irving K. Barber Faculty of ScienceCo-supervisorDr. Jeff Andrews, Irving K. Barber Faculty of ScienceSupervisory Committee MemberDr. Irene Vrbik, Irving K. Barber Faculty of ScienceSupervisory Committee MemberDr. Anas Chaaban, School of EngineeringUniversity ExamineriiAbstractThe COVID-19 pandemic has wreaked financial devastation for airlines. Astravel restrictions eases, it is important for airlines to gather and assess theopinions of passengers in order to meet new expectations. With the availabil-ity of online electronic platforms, it has become feasible to collect customerreviews on a large scale. Collecting, processing and deciphering textual dataremain a challenge to most. This thesis details the collection of textual re-view data from SkyTrax and Trip Advisor. Subsequently, it demonstratesthe use of quantitative sentiment scoring of the textual reviews, exploratorydata analysis and statistical modelling to ascertain factors that affect pas-senger perceptions of airlines services. Specifically, we developed a linearmixed model with passengers and airline as random to rank various airlineswith respect to sentiment scores, while confirming fixed factors which affectthese scores. The application of this model allows for interpretability to theexpectations and recommendati…
has type: Thesis/Dissertation
date issued: 2023-02
is shown at: 10.14288/1.0423179
language: eng
degree discipline: Computer Science
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Gill, Paramjit
type: Text
identifier URI: http://hdl.handle.net/2429/83687