Sentiment Analysis by using Recurrent Neural Network

4 Pages Posted: 11 Apr 2019

See all articles by Alpna Patel

Alpna Patel

Kamla Nehru Institute of Technology

Arvind Kumar Tiwari

Kamla Nehru Institute of Technology

Date Written: February 8, 2019

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.

Keywords: Sentiment Analysis, Deep Learning, Sentiment Classification, Machine Learning

Suggested Citation

Patel, Alpna and Tiwari, Arvind Kumar, Sentiment Analysis by using Recurrent Neural Network (February 8, 2019). Proceedings of 2nd International Conference on Advanced Computing and Software Engineering (ICACSE) 2019. Available at SSRN: https://ssrn.com/abstract=3349572 or http://dx.doi.org/10.2139/ssrn.3349572

Alpna Patel (Contact Author)

Kamla Nehru Institute of Technology ( email )

SULTANPUR
UTTAR PRADESH
SULTANPUR
India

Arvind Kumar Tiwari

Kamla Nehru Institute of Technology ( email )

SULTANPUR
UTTAR PRADESH
SULTANPUR
India

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