https://github.com/anty-filidor/network_diffusion_examples

Experimental repo for paper: 10.1109/DSAA54385.2022.10032425
https://github.com/anty-filidor/network_diffusion_examples

covid-19 influence-maximization interacting-phenomena multilayer-networks network-science

Last synced: about 1 month ago
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Experimental repo for paper: 10.1109/DSAA54385.2022.10032425

• Host: GitHub
• URL: https://github.com/anty-filidor/network_diffusion_examples
• Owner: anty-filidor
• License: gpl-3.0
• Created: 2021-01-17T23:05:52.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2022-04-11T14:39:52.000Z (almost 3 years ago)
• Last Synced: 2024-11-08T18:47:33.629Z (3 months ago)
• Topics: covid-19, influence-maximization, interacting-phenomena, multilayer-networks, network-science
• Language: Jupyter Notebook
• Homepage:
• Size: 665 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 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](https://codeocean.com/capsule/8807709)

### 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](http://multilayer.it.uu.se/datasets.html).

This code is published under GNU General Public License v3 (see `LICENSE` file).

Authors: Michał Czuba, Piotr Bródka