https://github.com/zuruoke/sentiment_analysis_for_amazon_reviews

Sentiment Analysis for Amazon Reviews
https://github.com/zuruoke/sentiment_analysis_for_amazon_reviews

Last synced: 8 months ago
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Sentiment Analysis for Amazon Reviews

• Host: GitHub
• URL: https://github.com/zuruoke/sentiment_analysis_for_amazon_reviews
• Owner: zuruoke
• Created: 2020-01-28T08:06:48.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-01-28T08:08:49.000Z (over 6 years ago)
• Last Synced: 2024-12-27T11:32:12.560Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 10.7 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Sentiment_Analysis_for_Amazon_Reviews

Amazon customer reviews about the products are one of the main reasons to attract customers on Amazon. 

It basically helps them understand almost every detail of the product. Since, consumers cannot physically inspect the product while shopping online, Amazon product review is the one they can trust in order to judge a product.

A research conducted by Dimensional Research claims that 90% of consumers online believe their purchasing choices are influenced by product reviews

The dataset I'll be using was aggregated from product reviews website - www.trustpilot.com & www.consumeraffairs.com containing each customers'comments and rating of a particular service

In this project, I'll build a model using Natural Language Processing (NLP) to perform sentiment analysis (predict whether a comment is positive or negative) on Amazon customer's comments on their services.

In this project, I'll:

1. Use Natural Language Processsing to prepare the data for Machine Learning

2. Train a model using a Classifier model

3. Evaluate the performance of the model