research-article

Influence identification of opinion leaders in social networks: : an agent-based simulation on competing advertisements

Authors:

Haomin Wang, and

Yiyi ZhaoAuthors Info & Claims

Volume 76, Issue C

Pages 227 - 242

https://doi.org/10.1016/j.inffus.2021.06.004

Published: 01 December 2021 Publication History

Highlights

•

Study interactive influence of competitive product information dissemination

•

Reveal evolution process of users' opinions with multiple advertisement opinion leaders

•

Numerical simulation for information diffusion mechanism of competitive products

Abstract

In social networks, factors that influence the spread of information are essential for companies to comprehend. This study uses the opinion dynamic theory to investigate the influence of multiple advertisement opinion leaders in social networks. We construct an integrated bounded confidence model to simulate the evolution of followers’ opinions under two advertisement opinion leaders. Through experimental simulation, we found that the weight of influence on advertisements has a dual effect on the evolution of followers’ opinions, and the probability that information is transmitted by opinion leaders has a significant impact on the evolution of collective opinions. The results show that, for competitive products, companies should properly understand the propaganda power of product advertisements and improve the probability of information being successfully transmitted by opinion leaders.

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Cited By

Chen JLi YKou GWang H(2024)Effect of three-stage cascade of opinion dynamics models in coupled networksNeurocomputing10.1016/j.neucom.2023.127176572:COnline publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1016/j.neucom.2023.127176
Jiang BZhao YDong JHu J(2024)Analysis of the influence of trust in opposing opinionsInformation Fusion10.1016/j.inffus.2023.102173104:COnline publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1016/j.inffus.2023.102173
Yan SSu QGong ZZeng XHerrera-Viedma E(2023)Online public opinion prediction based on rolling fractional grey model with new information priorityInformation Fusion10.1016/j.inffus.2022.10.01291:C(277-298)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.inffus.2022.10.012
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Influence identification of opinion leaders in social networks: an agent-based simulation on competing advertisements

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Published In

cover image Information Fusion

Information Fusion Volume 76, Issue C

Dec 2021

430 pages

ISSN:1566-2535

Issue’s Table of Contents

Copyright © 2021.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 December 2021

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Cited By

Chen JLi YKou GWang H(2024)Effect of three-stage cascade of opinion dynamics models in coupled networksNeurocomputing10.1016/j.neucom.2023.127176572:COnline publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1016/j.neucom.2023.127176
Jiang BZhao YDong JHu J(2024)Analysis of the influence of trust in opposing opinionsInformation Fusion10.1016/j.inffus.2023.102173104:COnline publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1016/j.inffus.2023.102173
Yan SSu QGong ZZeng XHerrera-Viedma E(2023)Online public opinion prediction based on rolling fractional grey model with new information priorityInformation Fusion10.1016/j.inffus.2022.10.01291:C(277-298)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.inffus.2022.10.012
Bonifazi GCauteruccio FCorradini EMarchetti MTerracina GUrsino DVirgili L(2023)A framework for investigating the dynamics of user and community sentiments in a social platformData & Knowledge Engineering10.1016/j.datak.2023.102183146:COnline publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1016/j.datak.2023.102183
Romero EChica MDamas SRand W(2023)Two decades of agent-based modeling in marketing: a bibliometric analysisProgress in Artificial Intelligence10.1007/s13748-023-00303-y12:3(213-229)Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1007/s13748-023-00303-y
Seyfosadat SRavanmehr R(2023)Systematic literature review on identifying influencers in social networksArtificial Intelligence Review10.1007/s10462-023-10515-256:Suppl 1(567-660)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1007/s10462-023-10515-2
Wei JJia YZhu HHong XHuang W(2022)Opinion Dynamics Model with Bounded Confidence and the Sleeper EffectComputational Intelligence and Neuroscience10.1155/2022/20927572022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/2092757
Giráldez-Cru JZarco CCordón O(2022)Analyzing the extremization of opinions in a general framework of bounded confidence and repulsionInformation Sciences: an International Journal10.1016/j.ins.2022.07.164609:C(1256-1270)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1016/j.ins.2022.07.164

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