Sentiment Analysis for Amazon Reviews to Identify Customer Interests.

Abstract

In the twenty-first century, consumers now frequently buy online and use reviews to judge the quality of the products they purchase. These reviews are also examined by businesses to enhance their offerings. In order to glean business insights from massive datasets, this study uses sentiment analysis on Amazon product reviews. To determine the specific subjects upon which the entire collection of reviews is predicated, an LDA model is created for the Amazon review dataset. Word frequencies for each topic are visualized by us. After determining which machine learning model is most appropriate for sentiment analysis, the analysis is carried out on a topic-by-topic basis. Using logistic regression, the themes derived from the LDA model are categorized as either positive or negative product review subjects. Analysis is done on both the positive and negative subjects.