/supracentrality

Eigenvector centrality for Multilayer, Multiplex and Temporal Networks

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

Supracentrality

Centrality Analysis for Multilayer, Multiplex and Temporal Networks

This Python code implements the experimental results described in the book chapter:

[1] https://arxiv.org/abs/1705.02305

The supracentrality framework is also described in

[2] D Taylor, MA Porter and PJ Mucha (2019) "Tunable eigenvector-based centralities for multiplex and temporal networks." arXiv preprint available at https://arxiv.org/abs/1904.02059.

[3] D Taylor, SA Myers, A Clauset, MA Porter and PJ Mucha (2017) "Eigenvector-based centrality measures for temporal networks." Multiscale Modeling & Simulation 15(1), 537-574.

The results shown in [2] and [3] were created using Matlab code.

To see the code for [2], go to the 'matlab_code' branch of this repository: https://github.com/taylordr/supracentrality/tree/matlab_code

To see the code for [3], go to https://github.com/taylordr/Temporal_Eigenvector_Centrality