Belief model of complex contagions on random networks

Yang Li, Hao Sun, Wanda Xiong and Genjiu Xu

Physica A: Statistical Mechanics and its Applications, 2021, vol. 567, issue C

Abstract: We proposed a belief model on random networks to explore the process of opinion dissemination, focusing on 3 significant factors: the inherent beliefs of individuals, the heterogeneity of individual persuasion ability and the dilution effect of neighbor size on neighbors’ persuasion. By mean-field approximation approach, the theoretical final fraction of active agents is determined, which agrees well with simulation results in most situations but diverges around critical condition. This divergence is demonstrated to be caused by the heterogeneity of properties of the initial active node and inevitable for any mean solution. As an alternative to predict and control the contagion, we proposed two strategies for selecting the initial active node based on its properties. Their efficiencies are discussed on different networks by simulations.

Keywords: Belief model; Complex contagion; Random networks (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437120309754
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:567:y:2021:i:c:s0378437120309754

DOI: 10.1016/j.physa.2020.125677

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().