SocialNetworkSimulation

This project simulates a social network using autonomous agents based on Large Language Models (LLMs) to study the emergence of influencers and information spread patterns.

Considerations

1. Having Python version greater than 3.9 and lower than 3.11.0

Setup

1. Clone the repository:

git clone https://github.com/nicolastorresr/SocialNetworkSimulation.git
cd SocialNetworkSimulation

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows, use venv\Scripts\activate

3. Install the required packages:

pip install -r requirements.txt

Running the Simulation

1. Configure the simulation parameters in config/simulation_config.yaml.

2. Run the simulation:

python scripts/run_simulation.py

4. Analyze the results:

python scripts/analyze_results.py

Project Structure

• src/: Contains the main source code
• agents/: Defines agent behaviors and types
• network/: Implements the social network structure
• simulation/: Contains the main simulation logic
• analysis/: Includes scripts for analyzing results
• config/: Contains configuration files
• data/: Stores raw and processed data from simulations
• notebooks/: Jupyter notebooks for data exploration and visualization
• tests/: Unit tests for various components
• scripts/: Executable scripts for running simulations and analysis

Running Tests

To run the unit tests:

python -m unittest discover tests

Contributing

Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.