Vol. 12 No. 1 (2024): Business & Management Studies: An International Journal
Articles

Analysis of environment-related reviews made about hotels using text mining: research on Antalya hotels

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  • Meryem Gürbüz,
  • Dilek Sürmeli,
  • Kamil Taşkın,
  • Halil İbrahim Cebeci
Meryem Gürbüz
Master Student., Sakarya University, Sakarya, Türkiye
Dilek Sürmeli
Lect., Sakarya Uygulamalı Bilimler University, Sakarya, Türkiye
Kamil Taşkın
Assoc. Prof. , Sakarya University, Sakarya, Türkiye
Halil İbrahim Cebeci
Assoc. Prof., Sakarya Üniversitesi, Sakarya, Türkiye
DOI: https://doi.org/10.15295/bmij.v12i1.2369

Published 2024-03-25

Keywords

  • Makine Öğrenmesi, Metin Madenciliği, Duygu Analizi, Yeşil Pazarlama, Turizm ve Konaklama
  • Machine Learning, Text Mining, Sentiment Analysis, Green Marketing, Tourism & Hospitality

How to Cite

Gürbüz, M., Sürmeli, D., Taşkın, K., & Cebeci, H. İbrahim. (2024). Analysis of environment-related reviews made about hotels using text mining: research on Antalya hotels. Business & Management Studies: An International Journal, 12(1), 218–239. https://doi.org/10.15295/bmij.v12i1.2369

Copyright (c) 2024 Meryem Gürbüz- Dilek Sürmeli- Kamil Taşkın- Halil İbrahim Cebeci

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Abstract

With the widespread use of the internet and the intensive use of social media, consumers can share their experiences about the products they use and service products such as hotels and restaurants through social media or the comment sections of websites. In recent years, analysing the increasing number of customer comments on the internet has become an essential resource for researchers and businesses. These traces in the virtual world accumulate over time and are collected by data scraping methods and analysed using text mining, machine learning, and sentiment analysis methods. The results obtained with these methods, which can be applied to different sectors, help businesses that pay attention to customer satisfaction make operational, tactical, and strategic decisions. In this context, in this study, the comments written in Turkish on the internet by approved users about the hotels in Antalya will be compiled using data scraping methods, categorised, and analysed using sentiment analysis. In this way, it is aimed to obtain vital information to improve hotel services and facilities and thus increase customer satisfaction by analysing customer comments. The dataset is first categorised into two groups, depending on whether it is related to the environment or not, using machine learning-based classification approaches. Then, sentiment analysis was performed on the dataset, and the findings were used to evaluate the environmental perceptions of customers about hotels. This study is an example of hotel managers developing business strategies by evaluating customer feedback. It also provides valuable information on how researchers can use text mining and sentiment analysis methods. The study analysed 180,478 comments about Antalya hotels and confidently concluded that customers' interest in environmental elements has increased and now plays a crucial role in hotel selection. It was observed that hotels prioritising environmental activities have significantly higher customer satisfaction. Environmental comments are generally negative in low-rated hotels but more balanced in high-rated hotels. Hotels should prioritise environmental activities to enhance customer satisfaction.

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