Sentiment Analysis of Amazon Product Review

Analysis sentiment also referred to as opinion mining, has become a crucial application of Natural Language Processing (NLP) in the modern digital era[1]. With the exponential rise of e-commerce platforms such as Amazon, millions of customers share their product experiences in the form of textual reviews. These reviews are valuable sources of information that can provide actionable insights for customers as well as businesses. However, manually analyzing such massive volumes of unstructured data is both time consuming and error-prone [4]. This paper proposes a framework for automated sentiment analysis of Amazon product reviews by leveraging machine learning (ML) and deep learning (DL) techniques. The system classifies reviews into positive, negative, or neutral sentiments and further provides summaries and visualizations to support decision-making. The methodology includes text preprocessing, feature extraction, sentiment classification using Support Vector Machines (SVM)[6] and Bidirectional Encoder Representations from Transformer.