论文标题

在上下文依赖性行为下在网络中传播动态

Spreading dynamics in networks under context-dependent behavior

论文作者

Burgio, Giulio, Gómez, Sergio, Arenas, Alex

论文摘要

在某些系统中,组成单元的行为可以创建一个“上下文”,以修改它们之间的直接交互。这种间接修改的机制促使我们开发了一种最小的上下文依赖性扩散模型。在我们的模型中,代理在相互作用过程中积极阻碍(偏爱)或不扩散,具体取决于他们在这种相互作用发生的组中所有同龄人中观察到的行为。我们将人口分为两种行为类型,并提供了一个平均场理论,以参数化任何大小组内的任意类型形成性的混合模式。作为应用程序,我们使用与上下文相关的预防性工具(例如面罩)进行了流行病扩散模型。通过分析组大小和类型组合的分布,我们发现了基本繁殖数和地方性状态的丰富现象学。我们通过分析显示,改变群体的组织如何促进或阻碍流行病的传播,最终将系统从亚临界阶段转移到超临界阶段,反之亦然,这主要取决于社会学因素,例如几乎没有或易于引起预防性行为。更一般而言,我们的工作为建模高阶环境并分析其动态含义提供了理论基础,并设想了与上下文相关相互作用的广泛理论,该理论将允许对各种复杂系统进行新的系统研究。

In some systems, the behavior of the constituent units can create a `context' that modifies the direct interactions among them. This mechanism of indirect modification inspired us to develop a minimal model of context-dependent spreading. In our model, agents actively impede (favor) or not diffusion during an interaction, depending on the behavior they observe among all the peers in the group within which that interaction occurs. We divide the population into two behavioral types and provide a mean-field theory to parametrize mixing patterns of arbitrary type-assortativity within groups of any size. As an application, we examine an epidemic spreading model with context-dependent adoption of prophylactic tools such as face-masks. By analyzing the distributions of groups' size and type-composition, we uncover a rich phenomenology for the basic reproduction number and the endemic state. We analytically show how changing the group organization of contacts can either facilitate or hinder epidemic spreading, eventually moving the system from the subcritical to the supercritical phase and vice versa, depending mainly on sociological factors, such as whether the prophylactic behavior is hardly or easily induced. More generally, our work provides a theoretical foundation to model higher-order contexts and analyze their dynamical implications, envisioning a broad theory of context-dependent interactions that would allow for a new systematic investigation of a variety of complex systems.

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