Sentiment Analysis of Customer Reviews

Sentiment analysis became a central driver of customer feedback understanding with the explosive increase of e-commerce websites such as Amazon. This paper brings together methodology and results from current studies that utilized machine learning algorithms based on Python to analyze sentiment within reviews of Amazon customers. The combination of different machine learning models, including deep neural network architectures, proved to show notable improvements in correctly classifying sentiments of customers.  the machine learning methods consist of Logistic Regression, Random Forest, SVM and Naive Bayes. Our dataset is composed of Amazon product reviews, where we utilize the star rating as a proxy for the sentiment expressed in each review. Through comprehensive experiments, we assess the performance of each model in terms of accuracy and effectiveness in detecting sentiment.