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A Case Study of Pyramid Scheme Finance Flow Network Based on Social Network Analysis

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  • Pihu Feng

    (College of Systems Engineering, National University of Defense Technology, Changsha 410072, China)

  • Duoyong Sun

    (College of Systems Engineering, National University of Defense Technology, Changsha 410072, China)

  • Zaiwu Gong

    (School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China)

Abstract

(1) Background: The pyramid scheme has caused a large-scale plunder of finances due to the unsustainability of its operating model, which seriously jeopardizes economic development and seriously affects social stability. In various types of networks, the finance flow network plays an extremely important role in the pyramid scheme organization. Through the study of the finance network, the operational nature of pyramid scheme organizations can be effectively explored, and the understanding of pyramid scheme organizations can be deepened to provide a basis for dealing with them. (2) Methods: This paper uses the motifs analysis and exponential random graph model in social network analysis to study the micro-structure and the network construction process of the “5.03” pyramid scheme finance flow network in Hunan, China. (3) Results: The finance flow network is sparse, the microstructure shows a typical pyramid structure; finance flows within the community and eventually flows to the most critical personnel, there is no finance relationship between different communities, and there are few finance relationships between pyramid salesmen of the same level. The inductees are in a key position in the network, which may explain why they are transferred to prosecution.

Suggested Citation

  • Pihu Feng & Duoyong Sun & Zaiwu Gong, 2019. "A Case Study of Pyramid Scheme Finance Flow Network Based on Social Network Analysis," Sustainability, MDPI, vol. 11(16), pages 1-12, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:16:p:4370-:d:257056
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    References listed on IDEAS

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    1. León, Carlos & Machado, Clara & Sarmiento, Miguel, 2018. "Identifying central bank liquidity super-spreaders in interbank funds networks," Journal of Financial Stability, Elsevier, vol. 35(C), pages 75-92.
    2. Affinito, Massimiliano & Franco Pozzolo, Alberto, 2017. "The interbank network across the global financial crisis: Evidence from Italy," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 90-107.
    3. Tiziano Squartini & Diego Garlaschelli, 2012. "Triadic motifs and dyadic self-organization in the World Trade Network," Papers 1201.1215, arXiv.org, revised Jan 2012.
    4. Handcock, Mark S. & Hunter, David R. & Butts, Carter T. & Goodreau, Steven M. & Morris, Martina, 2008. "statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i01).
    Full references (including those not matched with items on IDEAS)

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