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A novel approach to characterize information radiation in complex networks

Author

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  • Wang, Xiaoyang
  • Wang, Ying
  • Zhu, Lin
  • Li, Chao

Abstract

The traditional research of information dissemination is mostly based on the virus spreading model that the information is being spread by probability, which does not match very well to the reality, because the information that we receive is always more or less than what was sent. In order to quantitatively describe variations in the amount of information during the spreading process, this article proposes a safety information radiation model on the basis of communication theory, combining with relevant theories of complex networks. This model comprehensively considers the various influence factors when safety information radiates in the network, and introduces some concepts from the communication theory perspective, such as the radiation gain function, receiving gain function, information retaining capacity and information second reception capacity, to describe the safety information radiation process between nodes and dynamically investigate the states of network nodes. On a micro level, this article analyzes the influence of various initial conditions and parameters on safety information radiation through the new model simulation. The simulation reveals that this novel approach can reflect the variation of safety information quantity of each node in the complex network, and the scale-free network has better ”radiation explosive power”, while the small-world network has better ”radiation staying power”. The results also show that it is efficient to improve the overall performance of network security by selecting nodes with high degrees as the information source, refining and simplifying the information, increasing the information second reception capacity and decreasing the noises. In a word, this article lays the foundation for further research on the interactions of information and energy between internal components within complex systems.

Suggested Citation

  • Wang, Xiaoyang & Wang, Ying & Zhu, Lin & Li, Chao, 2016. "A novel approach to characterize information radiation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 94-105.
  • Handle: RePEc:eee:phsmap:v:452:y:2016:i:c:p:94-105
    DOI: 10.1016/j.physa.2016.01.076
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    References listed on IDEAS

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    Cited by:

    1. Fu, Chaoqi & Wang, Ying & Gao, Yangjun & Wang, Xiaoyang, 2017. "Complex networks repair strategies: Dynamic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 401-406.

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