Sentiment Analysis Of Movie Review Using Machine Learning

Abstract

This research applies sentiment analysis techniques to classify movie reviews from IMDB as positive or negative. The research involved analyzing sentiment analysis papers, studying classification algorithms, and collecting IMDB movie review data. The study utilizes or implements machine learning models like  KNN, SVM, Logistic Regression, and Random Forest on preprocessed movie review text. Key steps include feature extraction, sentiment expression examination, feature ranking, and training a multilevel classifier. By leveraging these methods, the approach achieves great accuracy in correctly classifying the sentiment polarity of IMDB movie reviews, demonstrating its effectiveness for this opinion-mining task on review data.