Temporal Network Analysis in Python

27 May 2015

Causality-driven slow-down and speed-up of diffusion in non-Markovian temporal networks

[2014]
Scholtes, Ingo; Wider, Nicolas; Pfitzner, Rene; Garas, Antonios; Tessone, Claudio Juan; Schweitzer, Frank

Nature Communications, pages: 5024, volume: 5

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We proudly present an in-depth educational tutorial showing how to analyze non-Markovian temporal networks using the python module pyTempNet which was recently developed at our chair. The tutorial features an interactive and hands-on introduction to our latest theoretical works on the analysis of time-stamped relational data. It demonstrates how our methods can be used to analyze the effect of order correlations in time-stamped network data, specifically showing how to analyze, simulate and visualize the effect of non-Markovian characteristics on dynamical processes.

The tutorial is available here.