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Modelling the stochastic dynamics of transitions between states in social systems incorporating self-organization and memory

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  • Zhukov, Dmitry
  • Khvatova, Tatiana
  • Millar, Carla
  • Zaltcman, Anastasia

Abstract

This conceptual research presents a new stochastic model of the dynamics of state-to-state transitions in social systems, the Zhukov–Khvatova model. Employing a mathematical approach based on percolation theory the model caters for random changes, system memory and self-organisation. Curves representing the approach of the system to the percolation threshold differ significantly from the smooth S-shaped curves predicted by existing models, showing oscillations, steps and abrupt steep gradients.

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  • Zhukov, Dmitry & Khvatova, Tatiana & Millar, Carla & Zaltcman, Anastasia, 2020. "Modelling the stochastic dynamics of transitions between states in social systems incorporating self-organization and memory," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    • Handle: RePEc:eee:tefoso:v:158:y:2020:i:c:s0040162520309604
    DOI: 10.1016/j.techfore.2020.120134
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    References listed on IDEAS

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    Cited by:

    1. Wu, Zhonghuan & Duan, Chunlin & Cui, Yuting & Qin, Rong, 2023. "Consumers' attitudes toward low-carbon consumption based on a computational model: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    2. Dmitry Zhukov & Julia Perova & Vladimir Kalinin, 2022. "Description of the Distribution Law and Non-Linear Dynamics of Growth of Comments Number in News and Blogs Based on the Fokker-Planck Equation," Mathematics, MDPI, vol. 10(6), pages 1-24, March.
    3. Zhukov, Dmitry & Khvatova, Tatiana & Millar, Carla & Andrianova, Elena, 2022. "Beyond big data – new techniques for forecasting elections using stochastic models with self-organisation and memory," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    4. Zhao, Jianyu & Yu, Lean & Xi, Xi & Li, Shengliang, 2023. "Knowledge percolation threshold and optimization strategies of the combinatorial network for complex innovation in the digital economy," Omega, Elsevier, vol. 120(C).

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