- GSI Journals Serie A: Advancements in Tourism Recreation and Sports Sciences
- Cilt: 7 Sayı: 1
- Comparison of Machine Learning Algorithms for Classification of Hotel Reviews: Sentiment Analysis of...
Comparison of Machine Learning Algorithms for Classification of Hotel Reviews: Sentiment Analysis of TripAdvisor Reviews
Authors : Hüseyin Ertan Inan
Pages : 111-122
Doi:10.53353/atrss.1327615
View : 153 | Download : 381
Publication Date : 2024-02-29
Article Type : Research
Abstract :Sentiment analysis can help extract meaningful information from these data piles from various websites and social media and measure consumers\' reactions by classifying consumers\' emotions as positive, negative or neutral. The success of sentiment analysis varies according to feature selection, vector space selection and machine learning method. For this reason, determining the most successful method in sentiment analysis is still controversial and important. A limited number of studies have been conducted comparing the success of various machine learning methods in sentiment analysis of hotel reviews in English. Considering this gap, the purpose of this research is to determine the most successful machine learning algorithm for sentiment analysis of hotel reviews. For this purpose, 708 reviews for 5-star hotels in Istanbul were collected manually. Obtained data were classified as positive and negative using logistic regression, k-nearest neighbor, naive Bayes and support vector machine methods. Analysis results show that the logistic regression method was the most successful classification algorithm, with an accuracy rate of 0.92. It is followed by support vector machine (0.90), naive Bayes method (0.77) and k-nearest neighbor algorithms (0.66).Keywords : Veri Madenciliği, Makine Öğrenmesi, Metin Madenciliği, Duygu Analizi, Otel Yorumları