CustomerInsight

Comprehensive Customer Review Analysis System

Features

🎯 Comprehensive Analysis Tools

• Sentiment Analysis with confidence scoring
• Keyword extraction and trend tracking
• Topic modeling and clustering
• Anomaly detection and deep insights

📊 Interactive Visualization

• Real-time data filtering and exploration
• Custom visualization options
• Dynamic trend analysis
• Comparative analytics

🌐 Multi-language Support

• Optimized for Chinese text
• English language compatibility
• Bilingual analysis capabilities

⚡ Performance & Scalability

• Efficient data processing
• Batch analysis support
• Caching for improved performance
• Error handling and validation

Getting Started

Prerequisites

• Python 3.7+
• Required packages:

pip install -r requirements.txt

Installation

1. Clone the repository:

git clone https://github.com/ChanMeng666/customer-insight.git
cd customer-insight

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment:

python setup.py install

Usage

Run the Streamlit application:

streamlit run app.py

The application will be available at http://localhost:8501

Technical Stack

📚 Core Technologies

• Frontend: Streamlit
• Data Processing: Pandas, NumPy
• Text Analysis:
  • Jieba (Chinese word segmentation)
  • Transformers (sentiment analysis)
  • scikit-learn (topic modeling)
• Visualization: Plotly, Matplotlib
• Machine Learning: scikit-learn

Features in Detail

Text Analysis

• Sentiment Analysis: Evaluate emotional tone of reviews
• Keyword Extraction: Identify key terms and phrases
• Topic Modeling: Discover underlying themes
• Anomaly Detection: Flag unusual patterns

Visualization

• Interactive time series plots
• Sentiment distribution charts
• Keyword clouds and trends
• Topic distribution maps

Data Processing

• Flexible data import (CSV, Excel)
• Advanced filtering options
• Text preprocessing
• Statistical analysis

Contributing

Contributions are welcome! Please feel free to submit pull requests.

License

This project is licensed under the Apache-2.0 license - see the LICENSE file for details.

Author

• Chan Meng
  • LinkedIn: chanmeng666
  • GitHub: ChanMeng666

Acknowledgments

• Thanks to all contributors who participated in this project
• Special thanks to the open source communities of Streamlit, Jieba, and other libraries used in this project