Higher-order aggregate networks in the analysis of temporal networks: path structures and centralities

  • Ingo Scholtes
  • Nicolas Wider
  • Antonios Garas
Regular Article
Part of the following topical collections:
  1. Topical issue: Temporal Network Theory and Applications


Despite recent advances in the study of temporal networks, the analysis of time-stamped network data is still a fundamental challenge. In particular, recent studies have shown that correlations in the ordering of links crucially alter causal topologies of temporal networks, thus invalidating analyses based on static, time-aggregated representations of time-stamped data. These findings not only highlight an important dimension of complexity in temporal networks, but also call for new network-analytic methods suitable to analyze complex systems with time-varying topologies. Addressing this open challenge, here we introduce a novel framework for the study of path-based centralities in temporal networks. Studying betweenness, closeness and reach centrality, we first show than an application of these measures to time-aggregated, static representations of temporal networks yields misleading results about the actual importance of nodes. To overcome this problem, we define path-based centralities in higher-order aggregate networks, a recently proposed generalization of the commonly used static representation of time-stamped data. Using data on six empirical temporal networks, we show that the resulting higher-order measures better capture the true, temporal centralities of nodes. Our results demonstrate that higher-order aggregate networks constitute a powerful abstraction, with broad perspectives for the design of new, computationally efficient data mining techniques for time-stamped relational data.


Betweenness Centrality Closeness Centrality Temporal Network Aggregate Network Reality Mining 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.ETH Zürich, Chair of Systems Design, Weinbergstrasse 56/58ZürichSwitzerland

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