Analyzing the channels of information dissemination: Investigating abrupt transitions in resource investment.

IF 3.3 2区 数学 Q1 MATHEMATICS, APPLIED Chaos Pub Date : 2025-01-01 DOI:10.1063/5.0250482
Yanan Wang, Taiming Wang, Yikang Lu, Xing Pan, Junpyo Park
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Abstract

Investment in resources is essential for facilitating information dissemination in real-world contexts, and comprehending the influence of resource allocation on information dissemination is, thus, crucial for the efficacy of collaborative networks. Nonetheless, current studies on information dissemination frequently fail to clarify the complex interplay between information distribution and resources in network contexts. In this work, we establish a resource-based information dissemination model to identify the complex interplay by examining the propagation threshold and equilibriums. We assess the model's efficacy by juxtaposing the mean-field method with Monte Carlo simulations across three author collaboration networks. In addition, we define the function of resources in information dissemination and evaluate the model's applicability using propagating threshold, time evolution, and parametric analyses. Our findings indicate that an increase in available resources accelerates and expands the distribution of information. Notably, we identify abrupt transition phenomena concerning available resources and demonstrate that the information self-learning rate and the information review rate hasten this transition, while information decline and re-diffusion rates decelerate it.

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信息传播渠道分析:资源投资突变现象研究。
资源投资对于促进现实环境中的信息传播至关重要,因此,理解资源配置对信息传播的影响对于协作网络的有效性至关重要。然而,目前关于信息传播的研究往往未能阐明网络环境下信息分布与资源之间复杂的相互作用。在这项工作中,我们建立了一个基于资源的信息传播模型,通过检查传播阈值和平衡来识别复杂的相互作用。我们通过将平均场方法与蒙特卡罗模拟并置于三个作者协作网络中来评估模型的有效性。此外,我们定义了资源在信息传播中的作用,并利用传播阈值、时间演化和参数分析来评估模型的适用性。我们的研究结果表明,可用资源的增加加速并扩大了信息的分布。值得注意的是,我们发现了可用资源的突变现象,并证明了信息自学习率和信息回顾率加速了这种转变,而信息下降和再扩散率减慢了这种转变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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