Class OpinionDynamics

java.lang.Object

org.episteme.social.sociology.OpinionDynamics

public final class OpinionDynamics
extends Object

Simulates opinion dynamics in social networks using various theoretical models. Includes implementations of the DeGroot model, Bounded Confidence (Deffuant-Weisbuch), and media influence models. Modernized to use Real for internal calculations and API.

Since:

1.0

Version:

1.2

Author:

Silvere Martin-Michiellot, Gemini AI (Google DeepMind)

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static final record	OpinionDynamics.Agent	Represents a single agent in the network with a specific opinion and stubbornness.
static final record	OpinionDynamics.SimulationState	Captures the state of the simulation at a specific step.

Method Summary

Modifier and Type	Method	Description
static Real	calculatePolarization(Map<String,Real> opinions)	Calculates a polarization index for the current opinion distribution.
static List<OpinionDynamics.SimulationState>	simulateBoundedConfidence(List<OpinionDynamics.Agent> agents, int steps, Real threshold, Real convergenceRate)	Runs the Bounded Confidence model (Deffuant-Weisbuch).
static List<OpinionDynamics.SimulationState>	simulateDeGroot(List<OpinionDynamics.Agent> agents, int steps)	Runs the DeGroot opinion dynamics model.
static List<OpinionDynamics.SimulationState>	simulateWithMedia(List<OpinionDynamics.Agent> agents, int steps, Real mediaOpinion, Real mediaInfluence)	Runs a social influence model incorporating external media effects.

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

simulateDeGroot

public static List<OpinionDynamics.SimulationState> simulateDeGroot(List<OpinionDynamics.Agent> agents,
 int steps)

Runs the DeGroot opinion dynamics model. In this model, agents update their opinions by taking the weighted average of their neighbors' opinions.

Parameters:

agents - initial configuration of agents

steps - number of simulation steps

Returns:

list of simulation states over time

simulateBoundedConfidence

public static List<OpinionDynamics.SimulationState> simulateBoundedConfidence(List<OpinionDynamics.Agent> agents,
 int steps,
 Real threshold,
 Real convergenceRate)

Runs the Bounded Confidence model (Deffuant-Weisbuch).

Parameters:

agents - initial configuration

steps - number of interaction steps

threshold - confidence threshold (epsilon) - Real

convergenceRate - rate of convergence (mu) - Real

Returns:

list of states (snapshot every 10 steps)

simulateWithMedia

public static List<OpinionDynamics.SimulationState> simulateWithMedia(List<OpinionDynamics.Agent> agents,
 int steps,
 Real mediaOpinion,
 Real mediaInfluence)

Runs a social influence model incorporating external media effects.

calculatePolarization

public static Real calculatePolarization(Map<String,Real> opinions)

Calculates a polarization index for the current opinion distribution.

Parameters:

opinions - map of agent opinions (Real)

Returns:

polarization score (Real)