Abstract
Sentiment analysis is the task of identifying opinions expressed in any form of text. With the widespread usage of social media in our daily lives, social media websites became a vital and major source of data about user reviews in various fields. The domain of tourism extended activity online in the most recent decade. In this paper, an approach is introduced that automatically perform sentiment detection using Fuzzy C-means clustering algorithm, and classify hotel reviews provided by customers from one of the leading travel sites. Hotel reviews have been analyzed using various techniques like Naïve Bayes, K-Nearest Neighbor, Support Vector Machine, Logistic Regression, and Random Forest. An ensemble learning model was also proposed that combines the five classifiers, and results were compared.
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Anis, S., Saad, S., Aref, M. (2021). Sentiment Analysis of Hotel Reviews Using Machine Learning Techniques. In: Hassanien, A.E., Slowik, A., Snášel, V., El-Deeb, H., Tolba, F.M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020. AISI 2020. Advances in Intelligent Systems and Computing, vol 1261. Springer, Cham. https://doi.org/10.1007/978-3-030-58669-0_21
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DOI: https://doi.org/10.1007/978-3-030-58669-0_21
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