Mining and Summarizing Movie Reviews in Mobile Environment

In this paper, we design and develop various strategies required for sentiment analysis of movie domain in mobile environment. The main objective of review mining and summarization is extracting the features on which the reviewers express their opinions and determining whether the opinions are positive or negative. The sentiment classification is done by various classifiers such as maximum entropy, naive bayes, Support vector machine (SVM) model and, Random forest technique, to name a few. Movie rating score based on sentiment classification result. The movie feature extraction is done by various methodologies such as Latent semantic analysis (LSA) algorithm and Frequency based algorithm. The result of LSA is extended to filtering mechanism to reduce the size of review summary. We design our system by consideration of sentiment classification accuracy & system response time. The same design can be extended to other product review domain easily. Keywords— natural language processing, movie reviews, summarization, sentiment classification.