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https://github.com/isatyamks/chatsense
This is my first machine learning model, designed to predict the mood and behavior of users by analyzing their WhatsApp chat archives.
https://github.com/isatyamks/chatsense
analysis artificial-intelligence behavior data-visualization machine-learning matplotlib pandas prediction seaborn vercel-deployment whatsapp-chat wordcloud
Last synced: 25 days ago
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This is my first machine learning model, designed to predict the mood and behavior of users by analyzing their WhatsApp chat archives.
- Host: GitHub
- URL: https://github.com/isatyamks/chatsense
- Owner: isatyamks
- Created: 2024-05-29T08:26:17.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-06-11T11:24:47.000Z (5 months ago)
- Last Synced: 2024-10-14T00:03:20.641Z (25 days ago)
- Topics: analysis, artificial-intelligence, behavior, data-visualization, machine-learning, matplotlib, pandas, prediction, seaborn, vercel-deployment, whatsapp-chat, wordcloud
- Language: Python
- Homepage:
- Size: 864 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
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README
# ChatSense - WhatsApp Chat Analyzer and Behavior Predictor
## Overview
This machine learning model aims to provide a simple but powerful tool for analyzing WhatsApp chat data. By utilizing some machine learning techniques, it not only provides insights into chat but in future i will make it to predict behaviors and moods based on the conversation history.
## Features
- **Chat Analysis**: Visualizes various aspects of WhatsApp chats, including message frequency and word usage.
- **Mood Prediction**: Uses machine learning to predict the mood or behavior of participants based on chat history.
- **Customizable Visualization**: Offers a range of visualization options using Matplotlib, Seaborn, and WordCloud.
- **Data Preprocessing**: Extracts URLs, emojis, and cleans text using regular expressions.
- **Easy Integration**: Can be integrated into existing projects or used as a standalone tool.
## Requirements
- Python 3.x
- Dependencies:
- `matplotlib`
- `pandas`
- `seaborn`
- `urlextract`
- `emoji`
- `wordcloud`
## Usage
1. **Install Dependencies**: Ensure Python 3.x is installed. Then, install the required packages:
```bash
pip install matplotlib pandas seaborn urlextract emoji wordcloud
```
2. **Prepare Data**: Export your WhatsApp chat history as a text file and place it in the `data_chats` folder. Update the `file` variable in `app.py` (line 7) with the relative path to your chat file.
3. **Run the Analyzer**: Execute the script to analyze your WhatsApp chat data:
```bash
python app.py
```
4. **Explore Results**: Review the generated visualizations and insights. Customize them as needed.
## Contributing
Contributions are welcome! To contribute:
1. Fork the repository.
2. Create a new branch: `git checkout -b feature/new-feature`.
3. Make your changes.
4. Commit your changes: `git commit -am 'Add new feature'`.
5. Push to the branch: `git push origin feature/new-feature`.
6. Create a Pull Request.
## Contact
For inquiries or feedback, please contact [Satyam Kumar](mailto:[email protected]) or connect on GitHub or LinkedIn.