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Hypex: A Tool for Extracting Business Intelligence from Sentiment Analysis using Enhanced LSTM

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Abstract

Sentiment analysis, an application of machine learning in business is the process of identifying and cataloging comments, reviews, tweets, feedback, and even random rants according to the tone or sentiments conveyed by it. The data is analysed using machine learning approach of Long Short Term Memory (LSTM) rating the sentiments on a scale ranging from −100 to 100. A new proposed activation function is used for LSTM giving best results as compared to the existing Artificial Neural Network (ANN) techniques. Depending upon the mined opinion, the business intelligence tools evaluate the products or services of a company eventually resulting in the increase of the sales of that company. The results clearly show that BI extracted from SA is quite instrumental in driving business effectiveness and innovation.

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Acknowledgments

The authors are sincerely thankful to the potential reviewers for their valuable comments and suggestions to improve the quality of the paper.

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Authors and Affiliations

  1. Indian Institute of Information Technology, Kota, India

    Ilayaraja Sreesurya & Himani Rathi

  2. Indian Institute of Information Technology, Nagpur, India

    Pooja Jain & Tapan Kumar Jain

Authors
  1. Ilayaraja Sreesurya
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  2. Himani Rathi
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  3. Pooja Jain
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  4. Tapan Kumar Jain
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Correspondence to Pooja Jain.

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Sreesurya, I., Rathi, H., Jain, P. et al. Hypex: A Tool for Extracting Business Intelligence from Sentiment Analysis using Enhanced LSTM. Multimed Tools Appl 79, 35641–35663 (2020). https://doi.org/10.1007/s11042-020-08930-6

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  • DOI: https://doi.org/10.1007/s11042-020-08930-6

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