Sentiment Analysis on Amazon Product Review

Abstract: This research analyzes the use of Natural Language Processing (NLP) with supervised machine learning methods to classify sentiments in Amazon product reviews. We applied extensive text preprocessing and transformed the dataset through TF-IDF vectorization of the Datafiniti Amazon Consumer Reviews dataset. A Linear Support Vector Classifier was used to determine the emotional classification of sentiments as Positive, Neutral, or Negative. The performance of the machine learning model is represented as evaluation results using confusion matrices as well as a classification report, following very good results for imbalanced data. In addition, the Power BI-generated trends over different product categories for sentiment visualization made the results quite interpretable and practically actionable for real-world e-commerce applications.