A matrix iteration for dynamic network summaries

P. Grindrod, D.J. Higham

Research output: Contribution to journalArticle

41 Citations (Scopus)
258 Downloads (Pure)

Abstract

We propose a new algorithm for summarizing properties of large-scale time-evolving networks. This type of data, recording connections that come and go over time, is generated in many modern applications, including telecommunications and online human social behavior. The algorithm computes a dynamic measure of how well pairs of nodes can communicate by taking account of routes through the network that respect the arrow of time. We take the conventional approach of downweighting for length (messages become corrupted as they are passed along) and add the novel feature of downweighting for age (messages go out of date). This allows us to generalize widely used Katz-style centrality measures that have proved popular in network science to the case of dynamic networks sampled at nonuniform points in time. We illustrate the new approach on synthetic and real data.
Original languageEnglish
Pages (from-to)118-128
Number of pages11
JournalSIAM Review
Volume55
Issue number1
DOIs
Publication statusPublished - 7 Feb 2013

Keywords

  • communicability
  • dynamic network
  • Katz centrality
  • social network analysis
  • telecommunication
  • resolvent

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