An interactive Sentiment Analysis Dashboard built with Streamlit, NLTK VADER, and Plotly for analyzing customer reviews across multiple E-commerce platforms (Amazon, BestBuy, eBay, Flipkart, Walmart, and Sixth Platform).
This project helps businesses understand customer opinions from product reviews by classifying them into positive, negative, and neutral sentiments with visual insights.
- ✅ Supports multiple e-commerce platforms (Amazon, BestBuy, eBay, Flipkart, Walmart, etc.)
- ✅ Sentiment classification using NLTK VADER
- ✅ Data preprocessing and cleaning with Pandas
- ✅ Interactive visualizations using Plotly Express
- ✅ Platform-wise sentiment distribution (Bar chart, Pie chart, 3D Line chart)
- ✅ Cross-platform sentiment comparison with 3D scatter plots
- ✅ Caching for optimized performance
📦 Sentiment-Analysis-Dashboard
├── app.py # Main Streamlit app
├── app_flask.py # Flask-based backend (optional)
├── analyzer.py # Sentiment analyzer logic
├── preprocess.py # Data preprocessing scripts
├── requirements.txt # Python dependencies
├── data/ # Folder containing datasets
│ ├── amazon_review.csv
│ ├── BestBut_Review.xlsx
│ ├── ebay_reviews.csv
│ ├── flipkart_product.csv
│ ├── wallmart_review.csv
│ └── sixth_file.csv
└── README.md # Project Documentation
The project uses customer review datasets from different e-commerce platforms:
amazon_review.csv→ Amazon reviewsBestBut_Review.xlsx→ BestBuy reviewsebay_reviews.csv→ eBay reviewsflipkart_product.csv→ Flipkart reviewswallmart_review.csv→ Walmart reviewssixth_file.csv→ Sixth Platform reviews
- Clone the repository
git clone https://github.com/KailashSatkuri-warangal/Sentiment-Analysis-Dashboard.git
cd Sentiment-Analysis-Dashboard- Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # Linux/Mac
venv\Scripts\activate # Windows- Install dependencies
pip install -r requirements.txt