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Uncovering-Customer-Satisfaction-through-Amazon-Product-Reviews

A Python project that uses Web Scraping techniques to extract product reviews from Amazon.com and performs sentiment analysis on the reviews to uncover customer satisfaction. The project focuses on extracting customer feedback from Amazon product pages to understand customer opinions and gather insights on how satisfied they are with the product.

Requirements

  • Python 3
  • BeautifulSoup
  • Pandas
  • Requests
  • NLTK

Getting Started

  • Clone the repository to your local machine using the following command:
git clone https://github.com/bsef19m521/Uncovering-Customer-Satisfaction-through-Amazon-Product-Reviews.git
  • Navigate to the project directory:
cd Uncovering-Customer-Satisfaction-through-Amazon-Product-Reviews
  • Installed the required packages:
pip install -r requirements.txt
  • Run the main Python script:
python3 main.py

Explanation of the code

The project consists of the following main steps:

  • Web scraping the Amazon product page to extract customer reviews.
  • Preprocessing the reviews by removing stopwords, punctuation marks, and HTML tags.
  • Performing sentiment analysis on the reviews using the NLTK library.
  • Plotting the results using visualizations to showcase customer satisfaction.

Contributions

Contributions are always welcome! Please feel free to raise an issue or submit a pull request if you find any bug or want to add a new feature.