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Can Social Contagion Spread Without Key Players?

机译:社会传染病是否可以在没有关键球员的情况下传播?

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Contagion models have been used to study the spread of social behavior among agents of a population, such as information diffusion, social influence, and participation to collective action (e.g., protests). Key players, which are typically high-degree, -k-core or -centrality agents in a networked population, are considered important for spreading social contagions. In this paper, we ask whether contagions can propagate through a population that is void of key players. We use Erdos-Renyi random graphs as a representation of unstructured populations that lack key players, and investigate whether complex contagions - those requiring reinforcement - can spread on them. We demonstrate that two game-theoretic contagion models that utilize common knowledge for collective action can readily spread such contagions, which is a significant difference from classic complex contagion models. We compare contagion dynamics results on unstructured networks to those on more typically-studied, structured social networks to understand the role of network structure. We test a total of 14 networks. The two common knowledge models are also contrasted to understand the effects of different modeling assumptions on dynamics. We show that under a wide range of conditions, these two models produce markedly different results.
机译:传染模式已被用于研究人口代理人的社会行为传播,例如信息扩散,社会影响和参与集体行动(例如,抗议)。关键参与者通常是网络人群中的高度,高核或性别的代理商,被认为是扩散社会凝视的重要性。在本文中,我们询问是否可以通过空隙的钥匙玩家的人口传播。我们使用Erdos-renyi随机图作为缺乏关键参与者的非结构化群体的代表,并调查复杂的凝聚是否是那些需要加强的群体 - 可以传播它们。我们展示了利用集体动作的共同知识的两个游戏理论传染模型可以容易地传播这些传染代价,这与经典复杂的传感器模型有重要差异。我们将Contagion Dynamics与非结构化网络的结果进行比较,以更典型地研究的,结构化的社交网络,以了解网络结构的作用。我们测试了14个网络。这两个常见的知识模型也与理解不同建模假设对动态的影响形成鲜明对比。我们表明,在广泛的条件下,这两种模型产生明显不同的结果。

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