Sentiment Analysis for IMDb Movie Review Using Support Vector Machine (SVM) Method

Many researchers currently employ supervised, machine learning methods to study sentiment analysis. Analysis can be done on movie reviews, Twitter online product blogs, discussion forums, Myspace comments, and social networks. Support Vector Machines (SVM) classifiers are used analyze the data set using different parameters. The analysis were undertaken allow for conclusion that SVM has been successfully implemented utilizing IMDb this (Support Machine). To complete study, preprocessing phase, which consisted of filtering classifying with a total 50.000 points, was completed after collecting up 40.000 reviews use as training 10.000 testing data. 25.000 positive negative points make view. In we adopted an evaluation matrix including accurate, precision, recall, F1-score. According experiment report, our model achieved Bags Word (BoW) get results highest accuracy test, 88,59% accurate. Then, grid-search, optimize against parameters find best models use. Our Term Frequency–inverse Document Frequency (TF-IDF) 91,27% accurate.