International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 4 (July-August 2026) Submit your research before last 3 days of August to publish your research paper in the issue of July-August.
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Volume 8 Issue 4
July-August 2026

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Sentiment Analysis on E-commerce Product Reviews using Deep Learning

Author(s) Ms. Mounika Garikapati, Mr. Nageswara Rao Kapu
Country India
Abstract With the rapid growth of e-commerce platforms, understanding customer feedback has become crucial for businesses to improve their products and services. Sentiment analysis, a subfield of Natural Language Processing (NLP), plays a vital role in extracting opinions from user-generated content such as product reviews. This project aims to perform sentiment analysis on e-commerce product reviews using a hybrid deep learning approach. A CNN-LSTM (Convolutional Neural Network - Long Short-Term Memory) model was implemented to classify customer reviews into positive and negative sentiments. The CNN layer effectively captures local features from the text, while the LSTM layer processes sequential dependencies for better contextual understanding. The dataset was preprocessed using techniques such as tokenization, stop word removal, and padding, followed by word embedding for semantic representation. Experimental results demonstrate that the CNN-LSTM model achieves an impressive accuracy of 95%, outperforming traditional machine learning models. The proposed model provides an efficient solution for automating sentiment classification in large-scale e-commerce platforms.
Keywords Sentiment Analysis, Natural Language Processing (NLP), CNN-LSTM, Deep Learning, E-commerce, Product Reviews, Text Classification, Opinion Mining.
Field Computer Applications
Published In Volume 8, Issue 4, July-August 2026
Published On 2026-07-31
DOI https://doi.org/10.36948/ijfmr.2026.v08i04.84864
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E-ISSN 2582-2160
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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