Mapping temporal-network percolation to weighted, static event graphs

Mikko Kivelä, Jordan Cambe, Jari Saramäki, Márton Karsai*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)
112 Downloads (Pure)

Abstract

The dynamics of diffusion-like processes on temporal networks are influenced by correlations in the times of contacts. This influence is particularly strong for processes where the spreading agent has a limited lifetime at nodes: disease spreading (recovery time), diffusion of rumors (lifetime of information), and passenger routing (maximum acceptable time between transfers). We introduce weighted event graphs as a powerful and fast framework for studying connectivity determined by time-respecting paths where the allowed waiting times between contacts have an upper limit. We study percolation on the weighted event graphs and in the underlying temporal networks, with simulated and real-world networks. We show that this type of temporal-network percolation is analogous to directed percolation, and that it can be characterized by multiple order parameters.

Original languageEnglish
Article number12357
Pages (from-to)1-9
JournalScientific Reports
Volume8
Issue number1
DOIs
Publication statusPublished - 1 Dec 2018
MoE publication typeA1 Journal article-refereed

Fingerprint Dive into the research topics of 'Mapping temporal-network percolation to weighted, static event graphs'. Together they form a unique fingerprint.

  • Equipment

    Science-IT

    Mikko Hakala (Manager)

    School of Science

    Facility/equipment: Facility

  • Cite this