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Sentiment Analysis by using Recurrent Neural Network

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Document pages: 4 pages

Abstract: Sentiment analysis is the process of emotion extraction and opinion mining from given text. This research paper gives the detailed overview of different feature selection methods, sentiment classification techniques and deep learning approaches for sentiment analysis. The feature selection methods include n-grams, stop words and negation handling. This paper also discusses about various sentiment classification techniques named as machine learning based approach and lexicon based approach. There is various classification algorithms such as SVM, Maximum Entropy and Naïve Bayes used for sentiment classification. In this paper we also discuss about deep learning models such as RNN, CNN and LSTM which is used for sentiment analysis. There are various application of sentiment analysis in decision making, prediction and business application.

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