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

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 Memor...

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Veröffentlicht in:Multimedia tools and applications 2020-12, Vol.79 (47-48), p.35641-35663
Hauptverfasser: Sreesurya, Ilayaraja, Rathi, Himani, Jain, Pooja, Jain, Tapan Kumar
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-020-08930-6