# ISOM5240 Project: Amazon Review Sentiment Analysis

## Team Members
- Jishen Wang
- Shen Yishan

## Project Structure
```
ISOM5240_Project/
├── README.md               # Project overview and setup instructions
├── requirements.txt        # Python dependencies
├── docs/                  # Documentation
│   ├── project_report.md  # Project report in markdown format
│   └── project_report.pdf # Project report in PDF format
├── src/                   # Source code
│   ├── app.py            # Streamlit web application
│   ├── model.py          # Sentiment analysis model implementation
│   ├── preprocessing.py  # Text preprocessing utilities
│   └── utils.py         # General utility functions
├── data/                 # Data directory for storing datasets
└── notebooks/           # Jupyter notebooks for analysis
```

## Setup Instructions
1. Clone this repository
2. Install dependencies:
```bash
pip install -r requirements.txt
```

## Running the Application
1. Navigate to the project directory:
```bash
cd ISOM5240_Project
```

2. Run the Streamlit application:
```bash
streamlit run src/app.py
```

3. Access the web interface at: http://localhost:8501

## Documentation
- Detailed project documentation can be found in the `docs` directory
- The project report is available in both markdown and PDF formats

## Model Information
- Using HuggingFace's LiYuan/amazon-review-sentiment-analysis model
- Multi-language support for sentiment analysis
- Real-time analysis through web interface

## Features
1. Sentiment analysis of product reviews
2. Multi-language support
3. Rating prediction (1-5 stars)
4. Web interface for real-time analysis
5. Batch processing capabilities
6. Results visualization and export options 

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference