A Sentiment analysis approach through deep learning for a movie review

This paper presents a study of various learning algorithms using sentiment analysis of movie reviews. Presently, posting reviews on movies is one of the famous approaches for expressing evaluations and grievances in the direction of the box office collection success brought or viewer comments received. The growing importance of sentiment analysis coincides with the growth of social media along with critiques, forum discussions, blogs, micro-blogs, Twitter, and social networks. The field of the sentiment of evaluation is intently tied to natural language processing and text mining. Sentiment Analysis, which is likewise called opinion mining, is the sphere of having a look at which analyzes human beings' reviews as thoughts to understand if the character was “glad”, “unhappy”, “angry” and so on. The essential goal of this paper is to illustrate the research on deep learning model by using Convolutional Neural Networks (CNN) with respect to supervised machine learning classifiers (Naïve Bayes, SVM, Logistic Regression, KNN and Ensemble Methods). The improvement in classification model accuracy through CNN classifier is presented as comparative analysis of their performance.