Analysis of Sentiment on Amazon Product Reviews

Sentiment Analysis is an essential process in the field of NLP (Natural Language Processing) that includes identifying the sentiment or emotion behind a text. Natural Language Processing (NLP) has a rapidly growing subfield called sentiment analysis that aims to determine the sentiment or emotion underlying a given text. Using the TF/IDF (Term Frequency-Inverse Document Frequency) and Logical Regression techniques, In this study, we did a sentiment analysis on user reviews of products on Amazon. This study aims to assess the tone of Amazon customer reviews and give significant information into how customers see the items. A customer review dataset was acquired from kaggle and preprocessed to remove noise and extraneous information. Utilizing the TF/IDF technique, features were extracted from the preprocessed reviews. Then, these characteristics were utilised to train a Logistic Regression classifier to predict the reviews' sentiment. Standard performance indicators such as accuracy, In order to evaluate the performance of the classifier of Logistic Regression, precision, recall, & F1 score have been used.