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Empirical Analysis of a Global Capital-Ownership Network

机译:全球资本所有权网络的实证分析

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Ownership relationships between legal entities can be represented as a large directed and weighted graph. This paper provides a methodology and an empirical analysis of such network, composed of millions of nodes and edges. To do so, we employ a variety of metrics from graph analytics and algorithms from influence maximization (IM). For reasons of confidentiality, our empirical analysis is carried out on aggregation at country and sector level, analysing in details the case of France. Our results offer new type of intuitions and metrics in this area by highlighting the existence of strong communities of capitalistic property. Finally, we discuss influence maximization methods as means to evaluate an entity impact in the socialistic graph.
机译:法律实体之间的所有权关系可以代表为大型指示和加权图。本文提供了由数百万节点和边缘组成的这种网络的方法和实证分析。为此,我们聘请了来自图分析和影响最大化(IM)的算法的各种指标。出于保密的原因,我们的实证分析是在国家和部门级别的聚合进行的,详细说明法国的案例。我们的业绩通过突出资本主义财产强大社区存在,提供新型的直觉和指标。最后,我们讨论了影响最大化方法作为评估社会主义图中实体影响的手段。

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