Sentiment Analysis of Ireland Hotel Reviews Using Machine Learning Techniques

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Nlemuzor, Paul
Issue Date
MSc in Business Analytics
Dublin Business School
Global internet usage and widespread acceptance of online review platforms play a vital role in individual and collective decision-making. These platforms are employed by users to express their sentiments based on a particular service they have utilized and write reviews. Moreover, the Ireland hotel business is rapidly developing and advancing and millions of individuals including tourists use the services rendered by these hotels. These tourists express their opinions and experiences in textual form that can be analyzed for business purposes and be useful to the Ireland hotel Industry. In this research, sentiment analysis has been employed to detect and classify sentiment polarity in hotel reviews, and different supervised machine learning techniques which include Support Vector Machine, Naïve Bayes, Random Forest and Logistic Regression were implemented and evaluated using accuracy, precision, recall and F1 score. Logistic regression and support vector machine outperformed the other models with an accuracy of 93%.