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Ponzi scheme diffusion in complex networks

Author

Listed:
  • Zhu, Anding
  • Fu, Peihua
  • Zhang, Qinghe
  • Chen, Zhenyue

Abstract

Ponzi schemes taking the form of Internet-based financial schemes have been negatively affecting China’s economy for the last two years. Because there is currently a lack of modeling research on Ponzi scheme diffusion within social networks yet, we develop a potential-investor–divestor (PID) model to investigate the diffusion dynamics of Ponzi scheme in both homogeneous and inhomogeneous networks. Our simulation study of artificial and real Facebook social networks shows that the structure of investor networks does indeed affect the characteristics of dynamics. Both the average degree of distribution and the power-law degree of distribution will reduce the spreading critical threshold and will speed up the rate of diffusion. A high speed of diffusion is the key to alleviating the interest burden and improving the financial outcomes for the Ponzi scheme operator. The zero-crossing point of fund flux function we introduce proves to be a feasible index for reflecting the fast-worsening situation of fiscal instability and predicting the forthcoming collapse. The faster the scheme diffuses, the higher a peak it will reach and the sooner it will collapse. We should keep a vigilant eye on the harm of Ponzi scheme diffusion through modern social networks.

Suggested Citation

  • Zhu, Anding & Fu, Peihua & Zhang, Qinghe & Chen, Zhenyue, 2017. "Ponzi scheme diffusion in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 128-136.
    • Handle: RePEc:eee:phsmap:v:479:y:2017:i:c:p:128-136
    DOI: 10.1016/j.physa.2017.03.015
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    References listed on IDEAS

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    Cited by:

    1. Dong, Tao & Wang, Aijuan & Zhu, Huiyun & Liao, Xiaofeng, 2018. "Event-triggered synchronization for reaction–diffusion complex networks via random sampling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 454-462.
    2. Wang, Aijuan & Liao, Xiaofeng & Dong, Tao, 2018. "Finite-time event-triggered synchronization for reaction–diffusion complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 111-120.
    3. Yong Shi & Bo Li & Wen Long, 2019. "A Pyramid Scheme Model Based on "Consumption Rebate" Frauds," Papers 1904.08136, arXiv.org, revised Jun 2019.
    4. Zhao, Narisa & Cheng, Xiaokang & Guo, Xianda, 2018. "Impact of information spread and investment behavior on the diffusion of internet investment products," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 427-436.
    5. Li Huang & Oliver Zhen Li & Yupeng Lin & Chao Xu & Haoran Xu, 2021. "Gender and age-based investor affinities in a Ponzi scheme," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-12, December.

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