Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted Network

In the realistic world, various individuals have distinct personalities, preferences, and attitudes toward new information and behavior acceptance, called population heterogeneity. It is seldom taken into account and theoretically analyzed in information propagation on a weighted network. Therefore,...

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Main Authors: Yajuan Cui, Yang Tian, Hui Tian, Gaofeng Nie, Shaoshuai Fan
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/4217101
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author Yajuan Cui
Yang Tian
Hui Tian
Gaofeng Nie
Shaoshuai Fan
author_facet Yajuan Cui
Yang Tian
Hui Tian
Gaofeng Nie
Shaoshuai Fan
author_sort Yajuan Cui
collection DOAJ
description In the realistic world, various individuals have distinct personalities, preferences, and attitudes toward new information and behavior acceptance, called population heterogeneity. It is seldom taken into account and theoretically analyzed in information propagation on a weighted network. Therefore, we divide individuals into fashionable and conservative individuals according to their passion degree and willingness for novel behaviors acceptance. Then, we build two behavior adoption threshold models corresponding to fashionable and conservative individuals on the weighted network to explore the effect of population heterogeneity on information propagation. Next, a partition theory based on edge weight and population heterogeneity is proposed to qualitatively analyze the information propagation mechanism. The theoretical analyses and simulation results show that fashionable individuals promote information propagation and behavior adoption. More importantly, the crossover phenomena of phase transition appear. When the fraction of fashionable individuals is relatively large, the increasing pattern of the final adoption size shows a second-order continuous phase transition. In comparison, the increasing pattern alters to first-order discontinuous phase transition with the decrease of the fraction of fashionable individuals. Moreover, reducing weight distribution heterogeneity promotes information propagation and slightly accelerates the change of the phase transition pattern from the first-order discontinuous to the second-order continuous. Besides, increasing the degree distribution heterogeneity accelerates the change of the phase transition pattern. Finally, our theoretical analyses coincide well with the simulation results.
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issn 1099-0526
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spelling doaj-art-4841ce115b7a41f090977853d791e1352025-08-20T02:38:01ZengWileyComplexity1099-05262022-01-01202210.1155/2022/4217101Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted NetworkYajuan Cui0Yang Tian1Hui Tian2Gaofeng Nie3Shaoshuai Fan4State Key Laboratory of Networking and Switching TechnologyState Key Laboratory of Networking and Switching TechnologyState Key Laboratory of Networking and Switching TechnologyState Key Laboratory of Networking and Switching TechnologyState Key Laboratory of Networking and Switching TechnologyIn the realistic world, various individuals have distinct personalities, preferences, and attitudes toward new information and behavior acceptance, called population heterogeneity. It is seldom taken into account and theoretically analyzed in information propagation on a weighted network. Therefore, we divide individuals into fashionable and conservative individuals according to their passion degree and willingness for novel behaviors acceptance. Then, we build two behavior adoption threshold models corresponding to fashionable and conservative individuals on the weighted network to explore the effect of population heterogeneity on information propagation. Next, a partition theory based on edge weight and population heterogeneity is proposed to qualitatively analyze the information propagation mechanism. The theoretical analyses and simulation results show that fashionable individuals promote information propagation and behavior adoption. More importantly, the crossover phenomena of phase transition appear. When the fraction of fashionable individuals is relatively large, the increasing pattern of the final adoption size shows a second-order continuous phase transition. In comparison, the increasing pattern alters to first-order discontinuous phase transition with the decrease of the fraction of fashionable individuals. Moreover, reducing weight distribution heterogeneity promotes information propagation and slightly accelerates the change of the phase transition pattern from the first-order discontinuous to the second-order continuous. Besides, increasing the degree distribution heterogeneity accelerates the change of the phase transition pattern. Finally, our theoretical analyses coincide well with the simulation results.http://dx.doi.org/10.1155/2022/4217101
spellingShingle Yajuan Cui
Yang Tian
Hui Tian
Gaofeng Nie
Shaoshuai Fan
Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted Network
Complexity
title Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted Network
title_full Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted Network
title_fullStr Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted Network
title_full_unstemmed Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted Network
title_short Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted Network
title_sort information propagation influenced by population heterogeneity behavioral adoption on weighted network
url http://dx.doi.org/10.1155/2022/4217101
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AT huitian informationpropagationinfluencedbypopulationheterogeneitybehavioraladoptiononweightednetwork
AT gaofengnie informationpropagationinfluencedbypopulationheterogeneitybehavioraladoptiononweightednetwork
AT shaoshuaifan informationpropagationinfluencedbypopulationheterogeneitybehavioraladoptiononweightednetwork