Empirical Analysis of a Global Capital-Ownership Network

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Abstract

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.

Original languageEnglish
Title of host publicationComplex Networks and Their Applications VIII - Volume 2 Proceedings of the 8th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019
EditorsHocine Cherifi, Sabrina Gaito, José Fernendo Mendes, Esteban Moro, Luis Mateus Rocha
PublisherSpringer
Pages656-667
Number of pages12
ISBN (Print)9783030366827
DOIs
Publication statusPublished - 1 Jan 2020
Event8th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2019 - Lisbon, Portugal
Duration: 10 Dec 201912 Dec 2019

Publication series

NameStudies in Computational Intelligence
Volume882 SCI
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

Conference

Conference8th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2019
Country/TerritoryPortugal
CityLisbon
Period10/12/1912/12/19

Keywords

  • Capitalistic graphs
  • Centrality measures
  • Complex networks
  • Graph degeneracy
  • Influence maximization
  • Legal entities

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