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IJSTR >> Volume 9 - Issue 3, March 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Deep Learning Based Twitter Users Classification Using Sentiment Analysis

[Full Text]

 

AUTHOR(S)

K. Sarvana Kumari, Dr. B. Manjula

 

KEYWORDS

Sentiment analysis, deep neural network, convolutional neural network, deep belief network.

 

ABSTRACT

Sentiment analysis is essential for social alignment, especially when there are many Twitter users nowadays. In every rational sense, each of the previous works is dependent on old classification systems, for example SVM, Naïve Bayes, etc. Starting from late, fundamental learning techniques have shown promising accuracy in this space about the body of tweets in English. In this article we propose the fundamental assessment that enormous learning structures apply to gather the sense of Twitter information. There are two colossal learning methods with regard to our evaluation: short-term memory (LSTM) and dynamic convolution neural network (DCNN). A preprocessing of certifiable information has been promoted. We also investigate the impact of word management on tweets. The results show that critical learning strategies classified old style structures in all aspects: Naïve Bayes and SVM, with the exception of Maximum entropy.

 

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