📌 Sentiment Analysis of Amazon Customer Reviews

This repository contains a Sentiment Analysis project that applies Natural Language Processing (NLP) techniques to classify Amazon customer reviews into positive, negative, or neutral sentiments.

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📖 Overview

Sentiment analysis helps businesses understand customer opinions and make data-driven decisions. This project uses TextBlob for computing sentiment polarity and subjectivity, while VADER (Valence Aware Dictionary and Sentiment Reasoner) classifies reviews. The pipeline includes:

• Data Preprocessing (Cleaning, Tokenization, Stopword Removal)
• Sentiment Classification using TextBlob & VADER
• Data Visualization for actionable insights

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🛠 Technology Stack

Tool/Library	Purpose
Python	Core Programming Language
NLTK	Natural Language Processing
TextBlob	Sentiment Analysis
VADER	Rule-based Sentiment Analysis
Matplotlib & Seaborn	Data Visualization
Pandas	Data Handling

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🚀 How to Use

🔹 Navigate into the Folder:

cd Sentiment-Analysis-of-Amazon-Customer-Reviews

🔹 Install Required Dependencies:

pip install -r requirements.txt

🔹 Run the Sentiment Analysis Script:

python sentiment_analysis.py

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📜 Contributions & Issues

• Feel free to fork the repository and submit pull requests.
• If you encounter any issues, report them via GitHub Issues.

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📧 Contact

For any inquiries, reach out via GitHub. 🚀

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🔹 Happy Analyzing! 📊💡