Modelling of Excitation Propagation for Social Interactions

  • Darius Plikynas
  • Aistis Raudys
  • Šarūnas Raudys
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8531)


This paper investigates regularities in excitation information propagation in social interaction. We use cellular automaton approach where it is assumed that social media is composed from tens of thousands of community agents. Each agent can transmit and get a signal from several nearest neighbours. Weighted sums of input signals after reaction delay are transmitted to the closest agents. The model’s originality consists in the exploitation of neuron-based agent schema with nonlinear activation function employed to determine the reaction delay, the agent recovery period, and algorithms that define cooperation of several excitable groups. In the grouped model, each agent group can send its excitation signal to other groups. The agents and their groups should acquire diverse media parameters of social media in order to ensure desirable for social media character of excitation wave propagation patterns. The novel media model allows methodical analysis of propagation of several competing novelty signals. Simulations are very fast and can be useful for understanding and control of the simulated human and agent-based social mediums, planning and performing social and economy research.


agents based modelling social medium excitation waves grouped populations propagation of novelties 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Darius Plikynas
    • 1
  • Aistis Raudys
    • 1
  • Šarūnas Raudys
    • 2
  1. 1.Research and Development CenterKazimieras Simonavicius UniversityVilniusLithuania
  2. 2.Faculty of Mathematics and InformaticsVilnius UniversityVilniusLithuania

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