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.

25
/ 100
Experimental

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.

No commits in the last 6 months.

Use this if you need to analyze a large volume of Amazon fine food reviews to identify trends, popular opinions, or areas for product improvement.

Not ideal if you're looking for real-time sentiment analysis or need to process reviews from platforms other than Amazon fine foods.

e-commerce-analytics customer-feedback product-analysis sentiment-analysis market-research
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 13 / 25

How are scores calculated?

Stars

7

Forks

2

Language

Python

License

Last pushed

May 05, 2020

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/blurred-machine/Amazon-Fine-Food-Review-Analysis-using-NLP-Techniques"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.