This userscript allows you to gather and analyze information about your own Amazon Reviews

AI-powered Amazon review analysis platform that detects fake reviews using machine learning

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Amazon reviews analysis system

Design a Sentiment Analyzer using machine learning on Amazon review dataset.

A sentiment analyzer for Amazon reviews using machine learning algorithms like Logistic Regression and Support Vector Machines.

🛍️ AI-powered e-commerce product analyzer with multi-platform support (Amazon/Flipkart), intelligent caching, price comparison, review aggregation, and LLM-powered Q&A. Built with FastAPI, React TS, LangGraph & Gemini.

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🛍️ SentiMart BERT-powered sentiment analysis system for Amazon product reviews with interactive dashboard and real-time processing capabilities achieving 90%+ accuracy. Tech Stack: Python • PyTorch • BERT • Streamlit • Scikit-learn Features: Sentiment classification • Real-time processing • Interactive dashboard • Business metrics

Review analyzer for Amazon.com which detects incoming trends and issues of existing functionality

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Scrapes the reviews from the product page and gives you Word-Clouds to better understand the reviews.

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Amazon customer review crawler and analyzer

AN AI REVIEW ANALYZER FOR AMAZON

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This project is to analyze and give a report based on customer reviews - Scrutiny

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ZORA - Sentiment Analyzer For product reviews of e-commerce platforms: Amazon & Flipkart.

A Product Review Sentiment Analyzer that automatically classifies Amazon/Yelp reviews as positive, negative, or neutral.

This Sentiment Analyzer reviews messages from Amazon Company as either positive, neutral or negative. Impressive.

Amazon Product Review Sentiment Analyzer : A Flask web application that scrapes Amazon product reviews using Selenium and performs sentiment analysis with the `roBERTa` model from Hugging Face. It provides insights into customer feedback by categorizing reviews into positive, neutral, and negative sentiments.

"Comments and Reviews Analyzer", aims to provide an automated system that analyzes user-generated content from YouTube and Amazon. The system is designed to provide valuable insights into the sentiments of comments on YouTube videos and reviews of products on Amazon.

The Product Sentiment Analyzer and Review Dashboard is a web-based application that collects product reviews from e-commerce websites such as Amazon and Flipkart using dynamic web scraping. The application analyzes the reviews using sentiment analysis techniques and displays the insights on an interactive dashboard.

"Review Insight Analyzer" is a web app that analyzes Amazon product reviews using sentiment analysis and tracks price changes over time. It helps users make smarter buying decisions with real-time review insights and price trends, combining web scraping, NLP, and data visualization in a user-friendly interface.

Sentiment Analyzer Based on Text Analysis A simple sentiment analysis tool built with Streamlit and Naive Bayes. It processes text data from IMDb, Amazon, and Yelp to predict whether a review is Positive or Negative. 🚀

This project has analyzed the Amazon Review dataset to find any motivating insight concerning heterogeneous recommendations and answer the following questions: • Which users reviewed products from several domains? • What are the pairs of domains connected via bridge users? • What is the relation between domains? • What is the accuracy of using a state-of-the-art sentiment analysis tool such as Social Mention and Sentiment Analyzer over the reviews and see whether the result is consistent with the numeric score system for the reviews (e.g., positive sentiment for reviews with five stars vs. negative sentiment for reviews with one star)

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