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Temporal networks: Characterization, motifs and spreading

Characterization, motifs and spreading
Authors: Kertész, János;

Temporal networks: Characterization, motifs and spreading

Abstract

Networks as scaffolds of complex systems are intrinsically dynamic: They grow and shrink, split and merge, as well as there are processes taking place on them like spreading phenomena. As long as the time scale of the change of the network is much slower than that of the processes a static network picture is adequate. When these scales get closer to each other, a different, dynamic approach is necessary. There is a class of networks, in which the connections between the nodes are only temporarily present-these are the temporal networks. Examples are communication networks, networks based on proximity or the networks of financial transactions. Here we briefly review the characteristics of such temporal networks with special emphasis on the motifs, i.e., small, typical spatio-temporal units. We also discuss the effect of time distributions of events on spreading in temporal networks.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
Average
Average
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