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Sentiment Analysis of Thai Online Product Reviews using Genetic Algorithms with Support Vector Machine |
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| รหัสดีโอไอ | |
| Creator | Rawisuda Tesmuang |
| Title | Sentiment Analysis of Thai Online Product Reviews using Genetic Algorithms with Support Vector Machine |
| Contributor | Nivet Chirawichitchai |
| Publisher | Faculty of Science and Technology, Rajamangala University of Technology Thanyaburi |
| Publication Year | 2563 |
| Journal Title | Progress in Applied Science and Technology |
| Journal Vol. | 10 |
| Journal No. | 2 |
| Page no. | ICT01 |
| Keyword | Genetic Algorithms, Sentiment Analysis, Support Vector Machine |
| URL Website | https://ph02.tci-thaijo.org/index.php/stj-rmutt/index |
| Website title | Progress in Applied Science and Technology |
| ISSN | 2730-3020 |
| Abstract | This research purposes sentiment analysis of Thai online product reviews for hotel room services, hotels, and resorts with a collection of 4,000 sample data sets. A Modeling with Genetic Algorithms with 4 machine learning methods is created. It consists of Support Vector Machine, Decision Tree, Na?ve-Bayes, and K-Nearest Neighbor to compare the effectiveness of each method in analyzing sentiment analysis of the online products. The experiment found that the use of Genetic Algorithms with support vector machines provide better classification accuracy than using vector support machines with an accuracy of 88.64% and the proposed model can effectively reduce the dimensions of the data. |
