Analysis Sentiment Based on IMDB Aspects from Movie Reviews using SVM
Keywords:Analysis Sentiment, Movie Reviews, IMDB, Support Vector Machine, TF-IDF
A movie is a spectacle that can be done at a relaxed time. Currently, there are many movies that can be watched via the internet or cinema. Movies that are watched on the internet are sometimes charged to watch so that potential viewers before watching a movie will read comments from users who have watched the movie. The website that is often used to view movie comments today is IMDB. Movie comments are many and varied on the IMDB website, we can see comments based on the star rating aspect. This causes users to have difficulty analyzing other users' comments. So, this study aims to analyze the sentiment of opinions from several comments from IMDB website users using the star rating aspect and will be classified using the support vector machine method (SVM). Sentiment analysis is a classification process to understand the opinions, interactions, and emotions of a document or text. SVM is very efficient for many applications in science and engineering, especially for classification (pattern recognition) problems. In addition to the SVM method, the TF-IDF technique is also used to change the shape of the document into several words. The results obtained by applying the SVM model are 79% accuracy, 75% precision, and 87% recall. The SVM classification is also superior to other methods, namely logistic regression.
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