Bangladesh Airlines Sentiment Review Dataset

Citation Author(s):
Khan Md.
Hasib
Ahsanullah University of Science and Technology
Nurul Akter
Towhid
Jahangirnagar University
Md. Golam Rabiul
Alam
BRAC University
Submitted by:
Khan Md. Hasib
Last updated:
Tue, 10/25/2022 - 14:32
DOI:
10.21227/6fg6-s460
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Abstract 

Air travel is one of the most used ways of transit in our daily lives. So it's no wonder that more and more people are sharing their experiences with airlines and airports using web-based online surveys. This dataset aims to do topic modeling and sentiment analysis on Skytrax (airlinequality.com) and Tripadvisor (tripadvisor.com) postings where there is a lot of interest and engagement from people who have used it or want to use it for airlines. The goal of individuals gathering at Skytrax and Tripadvisor is to make better decisions based on the actual experiences of other customers who have flown with airlines. We gathered online reviews submitted by consumers who have flown with Bangladesh airlines in the past. The dataset gives a view of customer online reviews in terms of Bangladesh Airlines that covers all the reviews from September 2018 to July 2021. In this dataset, both 519 online reviews are for domestic routes and 528 online reviews are for international route passengers online review and lastly, work on overall 1047 online reviews of Bangladesh Airlines. The second dataset are combining the Skytrax and Tripadvisor datasets, we arrived with 1095 review records for Bangladesh Airlines.

 

Instructions: 

The dataset contains the separate excel named BD-AD 1047 Reviews and BD-AD - 1095 Review Dataset. Each excel files contain the review data collected from the passengers. 

Anyone can use this dataset in their scientific paper and cite as: K. M. Hasib, N. A. Towhid and M. G. R. Alam, "Online Review based Sentiment Classification on Bangladesh Airline Service using Supervised Learning," 2021 5th International Conference on Electrical Engineering and Information Communication Technology (ICEEICT), 2021, pp. 1-6, doi: 10.1109/ICEEICT53905.2021.9667818.