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物理接近如何塑造复杂的社交网络。

How Physical Proximity Shapes Complex Social Networks.

机构信息

Technical University of Denmark, Lyngby, Denmark.

Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.

出版信息

Sci Rep. 2018 Dec 7;8(1):17722. doi: 10.1038/s41598-018-36116-6.

Abstract

Social interactions among humans create complex networks and - despite a recent increase of online communication - the interactions mediated through physical proximity remain a fundamental way for people to connect. A common way to quantify the nature of the links between individuals is to consider repeated interactions: frequently occurring interactions indicate strong ties, such as friendships, while ties with low weights can indicate random encounters. Here we focus on a different dimension: rather than the strength of links, we study physical distance between individuals when a link is activated. The findings presented here are based on a dataset of proximity events in a population of approximately 500 individuals. To quantify the impact of the physical proximity on the dynamic network, we use a simulated epidemic spreading processes in two distinct networks of physical proximity. We consider the network of short-range interactions defined as d [Formula: see text] 1 meter, and the long-range which includes all interactions d [Formula: see text] 10 meters. Since these two networks arise from the same set of underlying behavioral data, we are able to quantitatively measure how the specific definition of the proximity network - short-range versus long-range - impacts the resulting network structure as well as spreading dynamics in epidemic simulations. We find that the short-range network - consistent with the literature - is characterized by densely-connected neighborhoods bridged by weak ties. More surprisingly, however, we show that spreading in the long-range network is quite different, mainly shaped by spurious interactions.

摘要

人类之间的社交互动会形成复杂的网络,尽管最近在线交流有所增加,但通过物理接近度进行的互动仍然是人们建立联系的基本方式。一种常用的方法是通过考虑重复互动来量化个体之间联系的性质:频繁发生的互动表明存在紧密联系,如友谊关系,而权重较低的联系则可能表示随机相遇。在这里,我们关注的是一个不同的维度:我们研究的是链接被激活时个体之间的物理距离,而不是链接的强度。本文提出的研究结果基于一个约 500 人人群的接近事件数据集。为了量化物理接近度对动态网络的影响,我们在两个不同的物理接近度网络中使用模拟的传染病传播过程进行研究。我们考虑了定义为 d [Formula: see text] 1 米的短程交互网络,以及包含所有交互的远程网络 d [Formula: see text] 10 米。由于这两个网络都源于同一组基本行为数据,我们能够定量地衡量接近网络的特定定义——短程与远程——如何影响传染病模拟中产生的网络结构和传播动力学。我们发现,短程网络——与文献一致——的特点是密集连接的邻居之间存在弱连接。然而,更令人惊讶的是,我们表明,远程网络中的传播行为则非常不同,主要由虚假互动所塑造。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6cf9/6286340/32ffb2ce48f5/41598_2018_36116_Fig1_HTML.jpg

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