Amazon-Fine-Foods-Reviews and Amazon-Fine-Food-Review-Analysis-using-NLP-Techniques
About Amazon-Fine-Foods-Reviews
jcharit1/Amazon-Fine-Foods-Reviews
A series of NLP projects with the Amazon Fine Foods Revews dataset
This project helps e-commerce managers and content strategists quickly identify which customer reviews are most helpful. By analyzing simple text features like sentence count and readability, it takes raw customer review text and predicts how useful a new review will be to shoppers. The insights help improve customer satisfaction by ensuring high-quality reviews are easy to find, especially for new or less popular products.
About Amazon-Fine-Food-Review-Analysis-using-NLP-Techniques
blurred-machine/Amazon-Fine-Food-Review-Analysis-using-NLP-Techniques
This repository consists of analysis over Amazon fine food purchase reviews by customers. The data has been collected by Stanford Network Analysis Project(SNAP). This dataset consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.
This project helps e-commerce managers and product analysts understand customer sentiment from Amazon fine food reviews. By inputting raw review text, product information, and user details, you get insights into customer ratings and common themes in their feedback. This is ideal for anyone looking to quickly grasp what customers think about food products.
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