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

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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Main Authors: Linfeng Zhong, Xiaoyu Xue, Yu Bai, Jin Huang, Qing Cheng, Longyang Huang, Weijun Pan
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2021/4506012
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spelling doaj-ed6d21343d374793b23c704b61bf07642021-02-15T12:52:59ZengHindawi LimitedDiscrete Dynamics in Nature and Society1026-02261607-887X2021-01-01202110.1155/2021/45060124506012Information Spreading on Activity-Driven Temporal Networks with Two-Step MemoryLinfeng Zhong0Xiaoyu Xue1Yu Bai2Jin Huang3Qing Cheng4Longyang Huang5Weijun Pan6Civil Aviation Flight University of China, Guanghan 618307, ChinaCollege of Cybersecurity, Sichuan University, Chengdu 610065, ChinaCivil Aviation Flight University of China, Guanghan 618307, ChinaCivil Aviation Flight University of China, Guanghan 618307, ChinaCivil Aviation Flight University of China, Guanghan 618307, ChinaCivil Aviation Flight University of China, Guanghan 618307, ChinaCivil Aviation Flight University of China, Guanghan 618307, ChinaInformation 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.http://dx.doi.org/10.1155/2021/4506012
collection DOAJ
language English
format Article
sources DOAJ
author Linfeng Zhong
Xiaoyu Xue
Yu Bai
Jin Huang
Qing Cheng
Longyang Huang
Weijun Pan
spellingShingle Linfeng Zhong
Xiaoyu Xue
Yu Bai
Jin Huang
Qing Cheng
Longyang Huang
Weijun Pan
Information Spreading on Activity-Driven Temporal Networks with Two-Step Memory
Discrete Dynamics in Nature and Society
author_facet Linfeng Zhong
Xiaoyu Xue
Yu Bai
Jin Huang
Qing Cheng
Longyang Huang
Weijun Pan
author_sort Linfeng Zhong
title Information Spreading on Activity-Driven Temporal Networks with Two-Step Memory
title_short Information Spreading on Activity-Driven Temporal Networks with Two-Step Memory
title_full Information Spreading on Activity-Driven Temporal Networks with Two-Step Memory
title_fullStr Information Spreading on Activity-Driven Temporal Networks with Two-Step Memory
title_full_unstemmed Information Spreading on Activity-Driven Temporal Networks with Two-Step Memory
title_sort information spreading on activity-driven temporal networks with two-step memory
publisher Hindawi Limited
series Discrete Dynamics in Nature and Society
issn 1026-0226
1607-887X
publishDate 2021-01-01
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.
url http://dx.doi.org/10.1155/2021/4506012
work_keys_str_mv AT linfengzhong informationspreadingonactivitydriventemporalnetworkswithtwostepmemory
AT xiaoyuxue informationspreadingonactivitydriventemporalnetworkswithtwostepmemory
AT yubai informationspreadingonactivitydriventemporalnetworkswithtwostepmemory
AT jinhuang informationspreadingonactivitydriventemporalnetworkswithtwostepmemory
AT qingcheng informationspreadingonactivitydriventemporalnetworkswithtwostepmemory
AT longyanghuang informationspreadingonactivitydriventemporalnetworkswithtwostepmemory
AT weijunpan informationspreadingonactivitydriventemporalnetworkswithtwostepmemory
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