Article
Online Sentiment Analysis for E-commerce Reviews Using Data Science for Customer Feedback and Sentiment Classification
This study focuses on leveraging data science techniques for sentiment analysis in the realm of E-commerce Reviews. By employing machine learning and Natural Language Processing(NLP), the research aims to extract valuable insights from Customer Feedback, categorizing sentiments as positive, negative, or neutral. The iterative process involves experimentation with various models, such as Support Vector Machines, Naive Bayes, and transformer-based approaches like BERT. The goal is to empower e-commerce platforms to respond promptly to customer sentiments, identify popular products, and enhance overall user satisfaction through data-driven strategies.
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