Sentiment Analysis of Thai Online Product Reviews using Genetic Algorithms with Support Vector Machine

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Published: Nov 16, 2020
DOI: https://doi.org/10.14456/past.2020.8
Keywords:
Genetic Algorithms Sentiment Analysis Support Vector Machine

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Rawisuda Tesmuang
Faculty of Information Technology, Sripatum University
Nivet Chirawichitchai
Faculty of Information Technology, Sripatum University

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, Naïve-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.

Article Details

How to Cite
1.
Tesmuang R, Chirawichitchai N. Sentiment Analysis of Thai Online Product Reviews using Genetic Algorithms with Support Vector Machine. Prog Appl Sci Tech. [Internet]. 2020 Nov. 16 [cited 2024 May 5];10(2):7-13. Available from: https://ph02.tci-thaijo.org/index.php/past/article/view/241933
Issue
Vol. 10 No. 2 (2020): July - December 2020
Section
Information and Communications Technology
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Europe PMC

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