Research Article
Contextual Sentiment Analysis of Airbnb Customer Reviews in Albania: An Investigation of BERT-based Classification
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 187 - Issue 144 |
| Published: September 2026 |
| Authors: Blerina Zanaj, Serxhio Kurti, Elma Zanaj |
10.5120/ijcae9fc9e345d91
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Blerina Zanaj, Serxhio Kurti, Elma Zanaj . Contextual Sentiment Analysis of Airbnb Customer Reviews in Albania: An Investigation of BERT-based Classification. International Journal of Computer Applications. 187, 144 (September 2026), 19-26. DOI=10.5120/ijcae9fc9e345d91
@article{ 10.5120/ijcae9fc9e345d91,
author = { Blerina Zanaj,Serxhio Kurti,Elma Zanaj },
title = { Contextual Sentiment Analysis of Airbnb Customer Reviews in Albania: An Investigation of BERT-based Classification },
journal = { International Journal of Computer Applications },
year = { 2026 },
volume = { 187 },
number = { 144 },
pages = { 19-26 },
doi = { 10.5120/ijcae9fc9e345d91 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2026
%A Blerina Zanaj
%A Serxhio Kurti
%A Elma Zanaj
%T Contextual Sentiment Analysis of Airbnb Customer Reviews in Albania: An Investigation of BERT-based Classification%T
%J International Journal of Computer Applications
%V 187
%N 144
%P 19-26
%R 10.5120/ijcae9fc9e345d91
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This study evaluates sentiment analysis techniques for assessing tourist experiences with Airbnb accommodations in Albania by comparing textual reviews with conventional numerical ratings. Since star ratings may not fully capture the contextual and subjective aspects of customer experiences, Natural Language Processing (NLP) techniques are applied to extract sentiment from textual feedback. The study compares a BERT-based Transformer model with traditional machine-learning methods, including Support Vector Machine (SVM) and Naive Bayes. The experimental results indicate that BERT provides higher sentiment-classification performance, demonstrating its ability to capture contextual and semantic information in tourist reviews. The findings highlight the potential of BERT-based sentiment analysis to complement numerical ratings and provide more detailed insights into tourist satisfaction and accommodation service quality.
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