Computational Model Library

C/PA Model with Leaders (Dictator and Democrat stubborn and Democrat with feedback) (1.0.0)

This entry provides an Agent-Based Model (ABM) of opinion and tolerance dynamics in artificial societies, implemented in the frame of the Concord/Partial Antagonism (C/PA) model. This version is specifically designed to investigate the impact of asymmetric influence through two leadership archetypes—Dictator and Democrat—within networked societies.
The model is highly modular, allowing the user to simulate three distinct social scenarios:
Baseline C/PA: Self-organization of a society without external influence.
Stubborn Leadership: Introduction of a “solid conviction” leader (Dictator or Democrat) who exerts constant pressure without changing their own stance.
Feedback Leadership: A democratic leader receptive to social feedback, where the leader’s opinion evolves based on interactions with the population.
Theoretical Foundations:
The model is grounded in Social Influence, Social Judgment, and Social Identity theories. Social influence is represented by the overlap (hij) of agents’ opinion segments, while the psychological response to this influence is determined by the agent’s type: Concord (C) agents seek agreement, whereas Partial Antagonism (PA) agents can exhibit repulsive behavior if the ideological distance is too great.

Dynamics and Interaction:
The system consists of N=1000 agents plus one specialized leader node, embedded in a Small-World network. The interaction dynamics are stochastic, unidirectional, and asynchronous. In each time step, N edges are randomly selected. For each edge, an active (influential) agent and a passive (receptive) agent are assigned. If a positive psychological overlap exists (hij>0), the passive agent updates their opinion (x) and tolerance (u) following non-linear difference equations.
Simulation and Observation:
The model output is data that can generate final opinion histograms and 3-D bifurcation diagrams to analyze self-organization patterns such as consensus, polarization, and fragmentation. The primary output metric is Social Power (S), which can be quantified as the leader’s capacity to attract and stabilize a mass of followers as a function of the society’s average initial tolerance (U).

Release Notes

(fill later)

Associated Publications

C/PA Model with Leaders (Dictator and Democrat stubborn and Democrat with feedback) 1.0.0

This entry provides an Agent-Based Model (ABM) of opinion and tolerance dynamics in artificial societies, implemented in the frame of the Concord/Partial Antagonism (C/PA) model. This version is specifically designed to investigate the impact of asymmetric influence through two leadership archetypes—Dictator and Democrat—within networked societies.
The model is highly modular, allowing the user to simulate three distinct social scenarios:
Baseline C/PA: Self-organization of a society without external influence.
Stubborn Leadership: Introduction of a “solid conviction” leader (Dictator or Democrat) who exerts constant pressure without changing their own stance.
Feedback Leadership: A democratic leader receptive to social feedback, where the leader’s opinion evolves based on interactions with the population.
Theoretical Foundations:
The model is grounded in Social Influence, Social Judgment, and Social Identity theories. Social influence is represented by the overlap (hij) of agents’ opinion segments, while the psychological response to this influence is determined by the agent’s type: Concord (C) agents seek agreement, whereas Partial Antagonism (PA) agents can exhibit repulsive behavior if the ideological distance is too great.

Dynamics and Interaction:
The system consists of N=1000 agents plus one specialized leader node, embedded in a Small-World network. The interaction dynamics are stochastic, unidirectional, and asynchronous. In each time step, N edges are randomly selected. For each edge, an active (influential) agent and a passive (receptive) agent are assigned. If a positive psychological overlap exists (hij>0), the passive agent updates their opinion (x) and tolerance (u) following non-linear difference equations.
Simulation and Observation:
The model output is data that can generate final opinion histograms and 3-D bifurcation diagrams to analyze self-organization patterns such as consensus, polarization, and fragmentation. The primary output metric is Social Power (S), which can be quantified as the leader’s capacity to attract and stabilize a mass of followers as a function of the society’s average initial tolerance (U).

Release Notes

(fill later)

Version Submitter First published Last modified Status
1.0.0 Fernando Flores Briceño Tue Jul 28 05:48:22 2026 Tue Jul 28 05:48:24 2026 Published

Discussion

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept