Product Based Sentiment Analysis Based on Deep Learning for Amazon Review

The growth of E-commerce gave importance to customer needs and opinions which in turn gave rise to an important aspect of online shopping known as ‘Customer Reviews’. User reviews are customer suggestions and opinions about the product which helps other customers make decisions about the product. Such review systems form the backbone of Ecommerce. Using machine learning approach for sentiment analysis helps in finding useful patterns and derives predictions which are important in decision making for improvement of overall products and customer satisfaction. E-commerce websites generate thousands of reviews about different products on their website Sentiment Analysis is the process of identifying, extracting, and studying subjective knowledge using Natural Language Processing (NLP). The significance of sentiment analysis in understanding user-generated content, particularly in the context of Amazon product reviews. Our aim is to analyze the Amazon Customer Review Dataset using Aspect based sentiment analysis with Deep Learning Techniques and to uncover statistical trends, which can be used to improve customer satisfaction .The research evaluates multiple machine learning algorithms using a large dataset of Amazon reviews where BERT achieving the highest accuracy. Also we compare overall accuracy of these algorithms using measures like precision and recall and f measure.