Betweenness Preference: Quantifying Correlations in the Topological Dynamics of Temporal Networks

TL;DR

This paper introduces betweenness preference, a measure to quantify how the sequence of interactions in temporal networks affects the realizability of paths, impacting the analysis of dynamical processes.

Contribution

It presents a novel metric for analyzing correlations in temporal networks and demonstrates its significance using empirical data sets.

Findings

Betweenness preference is prevalent in real-world temporal networks.

Neglecting betweenness preference can lead to incorrect conclusions about network dynamics.

Betweenness preference influences shortest path lengths in temporal networks.

Abstract

We study correlations in temporal networks and introduce the notion of betweenness preference. It allows to quantify to what extent paths, existing in time-aggregated representations of temporal networks, are actually realizable based on the sequence of interactions. We show that betweenness preference is present in empirical temporal network data and that it influences the length of shortest time-respecting paths. Using four different data sets, we further argue that neglecting betweenness preference leads to wrong conclusions about dynamical processes on temporal networks.