This repository contains an implementation of the Linear Threshold Model (LTM) on various network topologies using D3.js for visualization. The available network topologies include random, small-world, and preferential attachment. You can adjust parameters such as the number of nodes, minimum and maximum thresholds, mean degree, rewiring probability, and attachment degree.
You can view and interact with the model here.
- Network Topologies: Choose between random, small-world, and preferential attachment topologies.
- Adjustable Parameters: Modify parameters like the number of nodes, threshold values, mean degree, rewiring probability, and attachment degree using sliders.
- Run Cascade: Visualize the cascade process in real-time.
- Network Statistics: View degree distribution, clustering coefficient distribution, and shortest path length distribution in the sidebar.
- Select Network Topology: Choose the desired network topology from the dropdown menu.
- Adjust Parameters: Use the sliders to set the number of nodes, minimum and maximum thresholds, and other relevant parameters.
- Generate and Run Cascade: Click the "Generate and Run Cascade" button to generate the network and start the cascade process.
- View Results: Observe the network visualization and the network statistics in the sidebar.
To run this project locally, follow these steps:
- Clone the repository:
git clone https://github.com/galenwilkerson/linear-threshold-model-on-network-topologies.git
- Navigate to the project directory:
cd linear-threshold-model-on-network-topologies - Open
ltm_cascade_topologies.htmlin a web browser.
Contributions are welcome! Please feel free to submit a pull request or open an issue if you have any suggestions or improvements.
This project is licensed under the MIT License. See the LICENSE file for details.