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社会交往网络中的社会经济相关性与分层

Socioeconomic correlations and stratification in social-communication networks.

作者信息

Leo Yannick, Fleury Eric, Alvarez-Hamelin J Ignacio, Sarraute Carlos, Karsai Márton

机构信息

Univ Lyon, ENS de Lyon, INRIA, CNRS, UMR 5668, IXXI, 69364 Lyon, France.

Univerisidad de Buenos Aires, Facultad de Ingeniería, Av. Paseo Colón 850, C1063ACV, Buenos Aires, Argentina.

出版信息

J R Soc Interface. 2016 Dec;13(125). doi: 10.1098/rsif.2016.0598.

DOI:10.1098/rsif.2016.0598
PMID:27974571
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5221523/
Abstract

The uneven distribution of wealth and individual economic capacities are among the main forces, which shape modern societies and arguably bias the emerging social structures. However, the study of correlations between the social network and economic status of individuals is difficult due to the lack of large-scale multimodal data disclosing both the social ties and economic indicators of the same population. Here, we close this gap through the analysis of coupled datasets recording the mobile phone communications and bank transaction history of one million anonymized individuals living in a Latin American country. We show that wealth and debt are unevenly distributed among people in agreement with the Pareto principle; the observed social structure is strongly stratified, with people being better connected to others of their own socioeconomic class rather than to others of different classes; the social network appears to have assortative socioeconomic correlations and tightly connected 'rich clubs'; and that individuals from the same class live closer to each other but commute further if they are wealthier. These results are based on a representative, society-large population, and empirically demonstrate some long-lasting hypotheses on socioeconomic correlations, which potentially lay behind social segregation, and induce differences in human mobility.

摘要

财富和个人经济能力的不均衡分布是塑造现代社会的主要力量之一,可以说这也使新兴社会结构产生了偏差。然而,由于缺乏大规模多模态数据来揭示同一人群的社会关系和经济指标,对个体社会网络与经济地位之间的相关性研究颇具难度。在此,我们通过分析耦合数据集来填补这一空白,该数据集记录了拉丁美洲一个国家100万匿名个体的手机通信和银行交易历史。我们发现,财富和债务在人群中的分布并不均衡,符合帕累托原则;观察到的社会结构具有强烈的分层现象,人们与同社会经济阶层的其他人联系更为紧密,而非与不同阶层的人;社会网络似乎存在社会经济相关性和紧密相连的“富人俱乐部”;并且来自同一阶层的个体彼此居住得更近,但如果他们更富有,通勤距离会更远。这些结果基于具有代表性的、涵盖整个社会的人群,并通过实证证明了一些关于社会经济相关性的长期假设,这些假设可能是社会隔离的潜在原因,并导致人类流动性的差异。