Open AccessSentiment Analysis of Movie Review using Machine Learning Approach
Author(s) -
Rajul Rai,
Pradeep Mewada
Publication year - 2017
Publication title -
international journal online of sports technology and human engineering
Language(s) - English
Resource type - Journals
ISSN - 2349-0772
DOI - 10.24113/ojssports.v5i1.83
Subject(s) - sentiment analysis , computer science , categorization , artificial intelligence , natural language processing , classifier (uml) , polarity (international relations) , the internet , ranking (information retrieval) , domain (mathematical analysis) , machine learning , information retrieval , world wide web , mathematical analysis , genetics , mathematics , cell , biology
With development of Internet and Natural Language processing, use of regional languages is also grown for communication. Sentiment analysis is natural language processing task that extracts useful information from various data forms such as reviews and categorize them on basis of polarity. One of the sub-domain of opinion mining is sentiment analysis which is basically focused on the extraction of emotions and opinions of the people towards a particular topic from textual data. In this paper, sentiment analysis is performed on IMDB movie review database. We examine the sentiment expression to classify the polarity of the movie review on a scale of negative to positive and perform feature extraction and ranking and use these features to train our multilevel classifier to classify the movie review into its correct label. In this paper classification of movie reviews into positive and negative classes with the help of machine learning. Proposed approach using classification techniques has the best accuracy of about 99%.