Scaling Properties in Time-Varying Networks with Memory

Abstract

The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

8 pages, 10 figures (published version)

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Cited by in corpus (5)

• Epidemic Spreading and Aging in Temporal Networks with Memory
• Effects of memory on spreading processes in non-Markovian temporal networks
• Dynamic topologies of activity-driven temporal networks with memory
• Impact of environmental changes on the dynamics of temporal networks
• Impact of temporal connectivity patterns on epidemic process