Analysis of Sentiment Employing the Word2vec with CNN-LSTM Classification System
- By Rajat Saini1
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View Affiliations Hide Affiliations1 Centre for Interdisciplinary Research in Business and Technology, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
- Source: Demystifying Emerging Trends in Machine Learning , pp 294-305
- Publication Date: February 2025
- Language: English
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The identification of problems has become easier in sentiment categorization using conventional neural networkbased short text classification methods . Word2vec, a convolutional neural network (CNN), and Bidirectional Long-term and Short-term Memory networks (LSTM) are used incombination to overcome this issue. Using Word2vec word embeddings, the CNN-LSTM model was able to attain an accuracy of 91.48%, as demonstrated experimentally. This demonstrates that the hybrid network model outperforms the single-structure neural network when dealing with relatively brief texts.
Hardbound ISBN:
9789815305401
Ebook ISBN:
9789815305395
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