dcmocanu / centrality-metrics-complex-networks

A repository for complex networks centrality metrics.

centrality-metrics-complex-networks

Proof of concept implementations of various centrality metrics for complex networks developed by us; The following implementations are distributed in the hope that they may be useful, but WITHOUT ANY WARRANTIES; Their use is entirely at the user's own risk.

Implementation 1 (game-of-thieves):

Game of Thieves (GoT) is a decentralized algorithm, inspired by swarm intelligence, which computes nodes and links centrality in complex networks or graphs; This code is a pre-alpha free software and was tested with Python 2.7.12, Matplotlib 2.1.0, Numpy 1.14, NetworkX 2.0; For an easy understanding of its behavior please read its corresponding article.

If you will use this code in your work please cite the article: @article{Mocanu2018GOT, author = {Mocanu, Decebal Constantin and Exarchakos, Georgios and Liotta, Antonio}, journal = {Scientific Reports}, title = {Decentralized dynamic understanding of hidden relations in complex networks}, volume = {8}, year = {2018}, doi = {10.1038/s41598-018-19356-4}, url = { https://www.nature.com/articles/s41598-018-19356-4 } }

GoT examples:

_ "game-of-thieves/example_GOT_illustration.py" is creating a nice visualization of GOT behavior (similar with Figure 1 from the paper);

_ "game-of-thieves/example_GOT_random_networks.py" is running GOT on a random generated network.