Empirical Analysis of a Global Capital-Ownership Network
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.
KeywordsComplex networks Legal entities Capitalistic graphs Centrality measures Graph degeneracy Influence maximization
- 2.Batagelj, V., Zaversnik, M.: An O(m) algorithm for cores decomposition of networks. arXiv preprint arXiv:cs/0310049 (2003)
- 4.Dijk, B.V.: Source: Orbis, bureau van dijkGoogle Scholar
- 5.Domingos, P., Richardson, M.: Mining the network value of customers. In: Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 57–66. ACM (2001)Google Scholar
- 7.Inaoka, H., Ninomiya, T., Taniguchi, K., Shimizu, T., Takayasu, H., et al.: Fractal network derived from banking transaction-an analysis of network structures formed by financial institutions. Bank of Japan Working Paper 4 (2004)Google Scholar
- 13.Tang, Y., Shi, Y., Xiao, X.: Influence maximization in near-linear time: a martingale approach. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 1539–1554. ACM (2015)Google Scholar