Comparison of Classification Algorithms for Movie Reviews
Korakot Matarat, Ariya Namvong, Chayada Surawanitkun · 2019
The objective of this research is to seek data mining techniques that are effective in classification and accurate at acceptable levels. Data from a movie review data set was tested using five algorithms, including Naïve Bayes, Decision Tree, Support Vector Machine, Artificial Neural Network, and k-Nearest Neighbor. Compared to other algorithms, it was found that the Support Vector Machine algorithm provided the highest accuracy of 80.20 percent. Based on this data, it suggested that this algorithm is suitable to analyze the review data that will be developed as a system to introduce products and services in the future.