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社会网络中同伴影响的起源。

Origin of peer influence in social networks.

机构信息

ATP Group, CMAF, Instituto para a Investigação Interdisciplinar, P-1649-003 Lisboa, Portugal and Centro de Física da Universidade do Minho, 4710-057 Braga, Portugal and INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, 2744-016 Porto Salvo, Portugal.

Departamento de Física and I3N, Universidade de Aveiro, 3810-193 Aveiro, Portugal.

出版信息

Phys Rev Lett. 2014 Mar 7;112(9):098702. doi: 10.1103/PhysRevLett.112.098702. Epub 2014 Mar 6.

Abstract

Social networks pervade our everyday lives: we interact, influence, and are influenced by our friends and acquaintances. With the advent of the World Wide Web, large amounts of data on social networks have become available, allowing the quantitative analysis of the distribution of information on them, including behavioral traits and fads. Recent studies of correlations among members of a social network, who exhibit the same trait, have shown that individuals influence not only their direct contacts but also friends' friends, up to a network distance extending beyond their closest peers. Here, we show how such patterns of correlations between peers emerge in networked populations. We use standard models (yet reflecting intrinsically different mechanisms) of information spreading to argue that empirically observed patterns of correlation among peers emerge naturally from a wide range of dynamics, being essentially independent of the type of information, on how it spreads, and even on the class of underlying network that interconnects individuals. Finally, we show that the sparser and clustered the network, the more far reaching the influence of each individual will be.

摘要

社交网络充斥着我们的日常生活

我们与朋友和熟人互动、相互影响。随着万维网的出现,大量关于社交网络的数据变得可用,从而可以对它们上面的信息分布进行定量分析,包括行为特征和时尚潮流。最近对具有相同特征的社交网络成员之间相关性的研究表明,个体不仅会影响他们的直接联系人,还会影响朋友的朋友,甚至会影响到超出他们最亲近的同伴的网络距离。在这里,我们展示了这种同伴之间相关性的模式是如何在网络人群中出现的。我们使用信息传播的标准模型(反映了内在不同的机制)来论证,在经验上观察到的同伴之间的相关模式是从广泛的动态中自然出现的,与信息的类型、它的传播方式以及连接个体的底层网络类别基本无关。最后,我们表明,网络越稀疏和聚类,每个个体的影响范围就越广泛。

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