Opinion mining is one of the new concepts of data mining. As World Wide Web is growing at higher rate, this has resulted in enormous increase in online communications. The online communication data consist of feedback, comments and reviews on particular topic that are posted on internet by internet users. Sentiment analysis is a sub-domain of opinion mining where the analysis is focused on the extraction of emotions, a specific view or judgment on certain topic. Sentiment analysis system classifies text data into their respective sentiments of positive polarity, negative polarity or neutral. In this domain most of the previous researchers have focused on using one of the three classifiers like SVM, Naïve Bayes, and Maximum Entropy. There are some other robust classifiers which have ability to provide comparable or better results. In this paper, we try to focus our task of sentimental analysis on “times of India” movie review database. We examine the sentiments present in the text document for classification of movie reviews based on polarity (positive/ negative/ neutral). Also we have used the Random Forest classifier for the evaluation of performance and for finding the accuracy. By using Random Forest classification technique we have achieved the best accuracy of 90%.


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    Title :

    Design approach for accuracy in movies reviews using sentiment analysis


    Contributors:


    Publication date :

    2017-04-01


    Size :

    383384 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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