Sentiment Analysis on Amazon Product Reviews using Deep Learning Models

Robert, Annjoys (2024) Sentiment Analysis on Amazon Product Reviews using Deep Learning Models. Masters thesis, Dublin, National College of Ireland.

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Abstract

This study introduces an approach, to analyzing customer sentiments in the realm of E-commerce titled "Sentiment Analysis on Amazon Product Reviews using Deep Learning Models". The main focus of this research is to extract insights from customer reviews by incorporating deep learning techniques. By utilizing a dataset consisting of over 568,000 reviews this study applies Convolutional Neural Networks (CNN) Recurrent Neural Networks (RNN) and Long Short Term Memory (LSTM) networks to classify sentiments. The LSTM model achieves an accuracy rate of up to 93.12%. Furthermore the project explores the effectiveness of BERT (Bidirectional Encoder Representations from Transformers) for sentiment analysis. Highlights its ability to predict sentiment in context despite its intensity. This research not contributes significantly to sentiment analysis in E-commerce. Also sheds light on the application and limitations of various deep learning models in natural language processing tasks.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Milosavljevic, Vladimir UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing H Social Sciences > HF Commerce > Marketing > Consumer Behaviour H Social Sciences > HF Commerce > Electronic Commerce Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	05 Jun 2025 13:20
Last Modified:	05 Jun 2025 13:20
URI:	https://norma.ncirl.ie/id/eprint/7758

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