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Experimental repo for paper: 10.1109/DSAA54385.2022.10032425

License: GNU General Public License v3.0

Python 1.68% Jupyter Notebook 98.32%
influence-maximization multilayer-networks network-science interacting-phenomena covid-19

network_diffusion_examples's Introduction

Network diffusion examples

Chosen examples for network_diffusion package

How to use

This code can be executed using CodeOcean capsule (step 1a), that suppress requirement of the runtime environment preparation from the user. Otherwise, the configuration of the workspace configuration will be essential (step 1b).

Step 1. option A

Navigate to this page

Step 1. option B

Create new python environment using requirements.txt file:

conda create --name nd_examples python=3.7
conda activate nd_examples
pip install -r requirements.txt

Create new ipython kernel from environment created above:

pip install ipykernel
ipython kernel install --user --name=nd_examples

Modify the output_dir variable in the config.ini file in order to point to the accessible directory.

Step 2.

Run one of following files in order to see results of experiments:

  • epidemic.py (example of epidemic propagation with auxiliary processes: vaccinations and awareness),
  • market_competition.ipynb (marketing campaign of two competitive products ),
  • gossip.ipynb (example of gossip spreading on two different social networks),
  • efficiency_tests/tests.ipynb (comparison of the network_diffusion time-efficiency)

Remarks

Please note that networks available in this directory have a source here.

This code is published under GNU General Public License v3 (see LICENSE file). Authors: Michał Czuba, Piotr Bródka

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