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Information accumulation system by inheritance and diffusion

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  • Shin, J.K.

Abstract

This paper suggests a new model, called as the IAS (Information Accumulation System), for the description of the dynamic process that people use to accumulate their information (knowledge or opinion) for specific issues. Using the concept of information, both the internal and the external mechanism of the opinion dynamics are treated on a unified frame. The information is quantified as a real number with fixed bounds. New concepts, such as inheritance and differential absorption, are incorporated in IAS in addition to the conventional diffusive interaction between people. Thus, the dynamics of the IAS are governed by following three factors: inheritance rate, diffusivity and absorption rate. The original set of equations was solved with an agent based modeling technique. In addition, the individual equations for each of the agents were assembled and transformed into a set of equations for the ensemble averages, which are greatly reduced in number and can be solved analytically. The example simulations showed interesting results such as the critical behavior with respect to diffusivity, the information polarization out of zero-sum news and the dependence of the solutions on the initial conditions alone. The results were speculated in relation to today’s modern society where the diffusivity of information has been greatly increased through the internet and mobile phones.

Suggested Citation

  • Shin, J.K., 2009. "Information accumulation system by inheritance and diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3593-3599.
  • Handle: RePEc:eee:phsmap:v:388:y:2009:i:17:p:3593-3599
    DOI: 10.1016/j.physa.2009.05.032
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    References listed on IDEAS

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    1. Jan Lorenz, 2007. "Continuous Opinion Dynamics Under Bounded Confidence: A Survey," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(12), pages 1819-1838.
    2. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    3. Serge Galam, 2008. "Sociophysics: A Review Of Galam Models," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 409-440.
    4. Sznajd-Weron, K. & Weron, R., 2003. "How effective is advertising in duopoly markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 437-444.
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    Cited by:

    1. Shin, J.K., 2010. "Tipping news in information accumulation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2118-2126.

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