Information Spreading on Activity-Driven Temporal Networks with Two-Step Memory

Information spreading dynamics on the temporal network is a hot topic in the field of network science. In this paper, we propose an information spreading model on an activity-driven temporal network, in which a node is accepting the information dependents on the cumulatively received pieces of infor...

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Published in:Discrete dynamics in nature and society 2021, Vol.2021, p.1-7
Main Authors: Zhong, Linfeng, Xue, Xiaoyu, Bai, Yu, Huang, Jin, Cheng, Qing, Huang, Longyang, Pan, Weijun
Format: Article
Language:English
Subjects:
Critical mass
Information management
Mathematical models
Network topologies
Numerical analysis
Numerical prediction
Outbreaks
Simulation
Social networks
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description Information spreading dynamics on the temporal network is a hot topic in the field of network science. In this paper, we propose an information spreading model on an activity-driven temporal network, in which a node is accepting the information dependents on the cumulatively received pieces of information in its recent two steps. With a generalized Markovian approach, we analyzed the information spreading size, and revealed that network temporality might suppress or promote the information spreading, which is determined by the information transmission probability. Besides, the system exists a critical mass, below which the information cannot globally outbreak, and above which the information outbreak size does not change with the initial seed size. Our theory can qualitatively well predict the numerical simulations.
doi_str_mv 10.1155/2021/4506012
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subjects Critical mass
Information management
Mathematical models
Network topologies
Numerical analysis
Numerical prediction
Outbreaks
Simulation
Social networks
title Information Spreading on Activity-Driven Temporal Networks with Two-Step Memory
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