Supracentrality

Centrality Analysis for Multilayer, Multiplex and Temporal Networks

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

[1] D Taylor, MA Porter and PJ Mucha (2019) "Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling" Book Chapter in "Temporal Network Theory", edited by P Holme and J Saramaki. [https://arxiv.org/abs/1906.06366]

The supracentrality framework is also described in the following papers

[2] D Taylor, MA Porter and PJ Mucha (2021) "Tunable eigenvector-based centralities for multiplex and temporal networks." Multiscale Modeling & Simulation 19(1), 113-147. [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. [https://arxiv.org/abs/1507.01266]

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

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

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