COMPLEX CONTAGION IN SOCIAL SYSTEMS WITH DISTRUST

IF 0.7 4区 数学 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
JEAN-FRANÇOIS DE KEMMETER, LUCA GALLO, FABRIZIO BONCORAGLIO, VITO LATORA, TIMOTEO CARLETTI
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引用次数: 0

Abstract

Social systems are characterized by the presence of group interactions and by the existence of both trust and distrust relations. Although there is a wide literature on signed social networks, where positive signs associated to the links indicate trust, friendship, agreement, while negative signs represent distrust, antagonism, and disagreement, very little is known about the effect that signed interactions can have on the spreading of social behaviors when, not only pairwise, but also higher-order interactions are taken into account. In this paper, we introduce a model of complex contagion on signed simplicial complexes, and we investigate the role played by trust and distrust on the dynamics of a social contagion process, where exposure to multiple sources is needed for the contagion to occur. The presence of higher-order signed structures in our model naturally induces new infection and recovery mechanisms, thus increasing the richness of the contagion dynamics. Through numerical simulations and analytical results in the mean-field approximation, we show how distrust determines the way the system moves from a state where no individuals adopt the social behavior, to a state where a finite fraction of the population actively spreads it. Interestingly, we observe that the fraction of spreading individuals displays a non-monotonic dependence with respect to the average number of connections between individuals. We then investigate how social balance affects social contagion, finding that balanced triads have an ambivalent impact on the spreading process, either promoting or impeding contagion based on the relative abundance of fully trusted relations. Our results shed light on the nontrivial effect of trust on the spreading of social behaviors in systems with group interactions, paving the way to further investigations of spreading phenomena in structured populations.

不信任社会系统中的复杂传染
社会系统的特点是存在群体互动以及信任和不信任关系。虽然已有大量关于符号社会网络的文献,其中与链接相关的正符号表示信任、友谊、一致,而负符号则表示不信任、对立和分歧,但人们对符号互动对社会行为传播的影响知之甚少,因为不仅要考虑成对互动,还要考虑高阶互动。在本文中,我们引入了一个关于签名简单复合物的复合物传染模型,并研究了信任和不信任对社会传染过程动态所起的作用。在我们的模型中,高阶符号结构的存在自然诱发了新的感染和恢复机制,从而增加了传染动力学的丰富性。通过均值场近似的数值模拟和分析结果,我们展示了不信任是如何决定系统如何从没有个体采取社会行为的状态转变为有限部分人群积极传播社会行为的状态的。有趣的是,我们观察到,传播个体的比例与个体之间的平均连接数呈非单调依赖关系。然后,我们研究了社会平衡如何影响社会传染,发现平衡的三人群体对传播过程具有矛盾的影响,根据完全信任关系的相对丰富程度,可以促进或阻碍传染。我们的研究结果揭示了在具有群体互动的系统中,信任对社会行为传播的非均衡影响,为进一步研究结构化群体中的传播现象铺平了道路。
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来源期刊
Advances in Complex Systems
Advances in Complex Systems 综合性期刊-数学跨学科应用
CiteScore
1.40
自引率
0.00%
发文量
121
审稿时长
6-12 weeks
期刊介绍: Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.
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