Noisy kinetic-exchange opinion model with aging

Area of Science:

• Complex systems
• Statistical physics
• Social dynamics

Background:

• Opinion dynamics models explore how collective opinions form and evolve.
• Agent-based models simulate individual interactions to understand emergent societal phenomena.
• The role of agent memory or 'aging' in opinion change is an emerging area of research.

Purpose of the Study:

• To investigate the critical behavior of a noisy kinetic opinion model incorporating agent aging.
• To analyze how different aging kernels (algebraic, exponential decay, anti-aging) influence opinion dynamics.
• To derive analytical predictions for critical curves and compare them with simulation results.

Main Methods:

• Development of a three-state (±1, 0) noisy kinetic opinion model.
• Mathematical analysis of opinion evolution with age-dependent interaction probabilities.
• Agent-based simulations on a complete graph to validate analytical predictions.

Main Results:

• Analytical predictions for critical curves of order parameters were derived.
• Simulations confirmed the accuracy of the analytical predictions.
• Weak aging was found to favor partial consensus compared to aging-insensitive models.
• Strong aging and anti-aging scenarios showed the opposite trend, reducing consensus.

Conclusions:

• Agent aging significantly modulates critical phenomena in opinion dynamics.
• The nature of the aging process (weak, strong, or anti-aging) dictates whether consensus is promoted or inhibited.
• The model provides a framework for understanding how memory effects influence collective opinion formation.