Modeling temporal networks with bursty activity patterns of nodes and links

Takayuki Hiraoka, Naoki Masuda, Aming Li, Hang Hyun Jo*

*この研究の対応する著者

研究成果査読

7 被引用数 (Scopus)

抄録

The concept of temporal networks provides a framework to understand how the interaction between system components changes over time. In empirical communication data, we often detect non-Poissonian, so-called bursty behavior in the activity of nodes as well as in the interaction between nodes. However, such reconciliation between node burstiness and link burstiness cannot be explained if the interaction processes on different links are independent of each other. This is because the activity of a node is the superposition of the interaction processes on the links incident to the node, and the superposition of independent bursty point processes is not bursty in general. Here we introduce a temporal network model based on bursty node activation, and we show that it leads to heavy-tailed interevent time distributions for both node dynamics and link dynamics. Our analysis indicates that activation processes intrinsic to nodes give rise to dynamical correlations across links. Our framework offers a way to model competition and correlation between links, which is key to understanding dynamical processes in various systems.

本文言語English
論文番号023073
ジャーナルPhysical Review Research
2
2
DOI
出版ステータスPublished - 2020 4
外部発表はい

ASJC Scopus subject areas

  • 物理学および天文学(全般)

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