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Public Opinion Evolution Based on Complex Networks Cover
By: Yeqing Zhao  
Open Access
|Mar 2015

Abstract

The Sznajd model of sociophysics can describe the mechanism of making a decision in a closed community. The Complex Agent Networks (CAN) model is studied, based on the adaptability, autonomy and activity of the individuals, as well as the complex interactions of individuals in an open community for probing into evolution of the public opinion. With the help of the theory of complex adaptive systems and the methods of complex networks, the structure of agents, the dynamic networks scenarios and the evolutionary process of the agents are described. The simulation results of CAN model show that all individuals cannot reach a final consensus through mutual consultations when the small world networks rewiring probability p is less than a specified threshold. But when the rewiring probability p is larger than the given threshold, all individuals will eventually come to a finial consensus, and that the rewiring probability p increases, whereas the time of emergence of the public opinion will be significantly reduced. It is quite obvious that in real community the mass media and many other mechanisms have an effect on the evolutionary process of the public opinion.

DOI: https://doi.org/10.1515/cait-2015-0006 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 55 - 68
Published on: Mar 13, 2015
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 Yeqing Zhao, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.