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Sentiment Analysis on Twitter Data by Using Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM)

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Abstract

Twitter sentiment analysis is an automated process of analyzing the text data which determining the opinion or feeling of public tweets from the various fields. For example, in marketing field, political field huge number of tweets is posting with hash tags every moment via internet from one user to another user. This sentiment analysis is a challenging task for the researchers mainly to correct interpretation of context in which certain tweet words are difficult to evaluate what truly is negative and positive statement from the huge corpus of tweet data. This problem violates the integrity of the system and the user reliability can be significantly reduced. In this paper, we identify the each tweet word and we are assigning a meaning into it. The feature work is combined with tweet words, word2vec, stop words and integrated into the deep learning techniques of Convolution neural network model and Long short Term Memory, these algorithms can identify the pattern of stop word counts with its own strategy. Those two models are well trained and applied for IMDB dataset which contains 50,000 movie reviews. With huge amount of twitter data is processed for predicting the sentimental tweets for classification. With the proposed methodology, the samples are experimentally collected from the real-time environment can be discriminated well and the efficacy of the system is improved. The result of Deep Learning algorithms aims to rate the review tweets and also able to identify movie review with testing accuracy as 87.74% and 88.02%.

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Authors and Affiliations

  1. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India

    Usha Devi Gandhi

  2. Department of Computer Science and Engineering, Kyung Hee University, Seoul, Korea

    Priyan Malarvizhi Kumar

  3. Vellore Institute of Technology, Vellore, India

    Gokulnath Chandra Babu

  4. School of Science and Technology, Middlesex University, London, England

    Gayathri Karthick

Authors
  1. Usha Devi Gandhi
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  2. Priyan Malarvizhi Kumar
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  3. Gokulnath Chandra Babu
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  4. Gayathri Karthick
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Correspondence to Priyan Malarvizhi Kumar.

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Gandhi, U.D., Malarvizhi Kumar, P., Chandra Babu, G. et al. Sentiment Analysis on Twitter Data by Using Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). Wireless Pers Commun (2021). https://doi.org/10.1007/s11277-021-08580-3

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  • DOI: https://doi.org/10.1007/s11277-021-08580-3

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