Social contagion under hybrid interactions

Xincheng Shu, Man Yang, Zhongyuan Ruan, Qi Xuan
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Abstract

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 hybrid 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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混合互动下的社会传染
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,我们研究了一个包含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支配的模仿行为(在博弈论框架下)。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,并伴随着混合阶段的转变。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,在采用的负报酬情况下,结果恰恰相反。这个模型可以为理解现实世界社交网络中社会传染现象的复杂动力学提供有价值的见解。
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