This paper introduces a novel numerical simulation model that represents the understanding and cognition of information on social networks as continuous phase field variables. The model defines opinion inclinations as phase field variables q_A, q_B, q_C, and incorporates the characteristics of social media communication, such as immediacy and bidirectionality, to dynamically reproduce the propagation of information and feedback mechanisms.
The simulation incorporates principles from sociophysics, including the existence of critical thresholds in societal behaviors, and simulates internal judgment conditions such as confirmation bias, social influence, forgetfulness, and opinion rigidity as parameters. This allows for a numerical analysis of how individual users process information and how opinions evolve as a result.
Furthermore, the model describes the phase separation dynamics of information between filter bubbles and non-bubble regions, detailing the interactions and evolution of opinions at the boundaries of spaces with different information concentrations. The spatial distribution of opinions and their dynamics under conditions where different opinions coexist and interact are simulated from the perspective of phase separation and interaction energy.
The study utilizes the Cahn-Hilliard equation, Ginzburg-Landau, Allen-Cahn equation, and phase field models to extend the theoretical framework to accommodate the multi-component system of opinion dynamics. This provides a sophisticated model that captures the nuances of opinion formation and evolution in non-equilibrium social systems, offering insights into the mechanisms of opinion polarization and echo chamber formation on social media.
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Önemli Bilgiler Şuradan Elde Edildi
by Yasuko Kawah... : arxiv.org 04-24-2024
https://arxiv.org/pdf/2311.03137.pdfDaha Derin Sorular