Mapping temporal-network percolation to weighted, static event graphs

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Kivelä, Mikko Cambe, Jordan Saramäki, Jari Karsai, Márton 2018-09-04T11:14:35Z 2018-09-04T11:14:35Z 2018-12-01
dc.identifier.citation Kivelä , M , Cambe , J , Saramäki , J & Karsai , M 2018 , ' Mapping temporal-network percolation to weighted, static event graphs ' Scientific Reports , vol 8 , no. 1 , 12357 , pp. 1-9 . DOI: 10.1038/s41598-018-29577-2 en
dc.identifier.issn 2045-2322
dc.identifier.other PURE UUID: f65cab03-b4f0-455b-8846-c8376c72dbdd
dc.identifier.other PURE ITEMURL:
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dc.description.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. en
dc.format.extent 1-9
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries Scientific Reports en
dc.relation.ispartofseries Volume 8, issue 1 en
dc.rights openAccess en
dc.subject.other General en
dc.subject.other 113 Computer and information sciences en
dc.title Mapping temporal-network percolation to weighted, static event graphs en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Computer Science
dc.contributor.department Aalto University
dc.subject.keyword General
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201809044950
dc.identifier.doi 10.1038/s41598-018-29577-2
dc.type.version publishedVersion

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