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Complexity of a Microblogging Social Network in the Framework of Modern Nonlinear Science

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  • Andrey Dmitriev
  • Vasily Kornilov
  • Svetlana Maltseva

Abstract

Recent developments in nonlinear science have caused the formation of a new paradigm called the paradigm of complexity. The self-organized criticality theory constitutes the foundation of this paradigm. To estimate the complexity of a microblogging social network, we used one of the conceptual schemes of the paradigm, namely, the system of key signs of complexity of the external manifestations of the system irrespective of its internal structure. Our research revealed all the key signs of complexity of the time series of a number of microposts. We offer a new model of a microblogging social network as a nonlinear random dynamical system with additive noise in three-dimensional phase space. Implementations of this model in the adiabatic approximation possess all the key signs of complexity, making the model a reasonable evolutionary model for a microblogging social network. The use of adiabatic approximation allows us to model a microblogging social network as a nonlinear random dynamical system with multiplicative noise with the power-law in one-dimensional phase space.

Suggested Citation

  • Andrey Dmitriev & Vasily Kornilov & Svetlana Maltseva, 2018. "Complexity of a Microblogging Social Network in the Framework of Modern Nonlinear Science," Complexity, Hindawi, vol. 2018, pages 1-11, December.
    • Handle: RePEc:hin:complx:4732491
    DOI: 10.1155/2018/4732491
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    1. Dubovikov, M.M & Starchenko, N.V & Dubovikov, M.S, 2004. "Dimension of the minimal cover and fractal analysis of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 591-608.
    2. Olemskoi, Alexander I. & Khomenko, Alexei V. & Kharchenko, Dmitrii O., 2003. "Self-organized criticality within fractional Lorenz scheme," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 263-293.
    3. Anders Mollgaard & Joachim Mathiesen, 2015. "Emergent User Behavior on Twitter Modelled by a Stochastic Differential Equation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-12, May.
    4. Benjamin Paul Chamberlain & Josh Levy-Kramer & Clive Humby & Marc Peter Deisenroth, 2018. "Real-time community detection in full social networks on a laptop," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-37, January.
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    Cited by:

    1. Andrey Dmitriev & Victor Dmitriev & Stepan Balybin, 2019. "Self-Organized Criticality on Twitter: Phenomenological Theory and Empirical Investigation Based on Data Analysis Results," Complexity, Hindawi, vol. 2019, pages 1-16, December.

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