混合互动下的社会传染

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Xincheng Shu, Man Yang, Zhongyuan Ruan, Qi Xuan
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引用次数: 0

摘要

阈值驱动模型和博弈论是描述社会系统中人类互动的两个基本范式。然而,在模仿社会传染过程中,同时包含这两种机制的模型在很大程度上被忽视了。在这里,我们研究了一个整合了混合互动形式的一般模型,假设网络中的部分节点受阈值机制驱动,而其余节点则表现出受其理性(博弈论框架下)支配的模仿行为。我们的研究结果表明,传播动态是由采用的报酬决定的。对于正报酬,增加高理性节点的密度可以促进采用过程,并伴随着双重阶段转换。理性程度可以调节传播速度,理性程度较低的模仿者会减缓传播速度。我们进一步发现,采用的负报酬结果正好相反。该模型可为理解现实世界社交网络中社会传染现象的复杂动态提供有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social contagion under hybrid interactions
Threshold-driven models and game theory are two fundamental paradigms for describing human interactions in social systems. However, in mimicking social contagion processes, models that simultaneously incorporate these two mechanisms have been largely overlooked. Here, we study a general model that integrates hybrid interaction forms by assuming that a part of nodes in a network are driven by the threshold mechanism, while the remaining nodes exhibit imitation behavior governed by their rationality (under the game-theoretic framework). Our results reveal that the spreading dynamics are determined by the payoff of adoption. For positive payoffs, increasing the density of highly rational nodes can promote the adoption process, accompanied by a double phase transition. The degree of rationality can regulate the spreading speed, with less rational imitators slowing down the spread. We further find that the results are opposite for negative payoffs of adoption. This model may provide valuable insights into understanding the complex dynamics of social contagion phenomena in real-world social networks.
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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