Psychological Parameters for Crowd Simulation: From Audiences to Mobs.

Area of Science:

• Social Psychology
• Computational Social Science
• Agent-Based Modeling

Background:

• Crowds are categorized in social psychology as either passive audiences or active, emotional mobs.
• Mobs exhibit irrational and homogeneous behavior, often leading to collective misbehavior.
• Existing models often lack the granularity to differentiate nuanced crowd dynamics.

Purpose of the Study:

• To develop a computational system for specifying and simulating various crowd types, ranging from audiences to mobs.
• To parameterize key mob properties contributing to collective misbehavior.
• To associate psychological components with individual agents to generate emergent crowd behaviors.

Main Methods:

• Developed a framework linking psychological components of individual agents to emergent crowd behavior.
• Parametrized common properties associated with mob behavior and collective misbehavior.
• Utilized agent-based modeling to simulate distinct mob types.

Main Results:

• Successfully created a system capable of simulating different crowd types based on specified parameters.
• Demonstrated the framework's effectiveness through two distinct mob behavior scenarios.
• Validated the association between individual psychological states and emergent collective actions.

Conclusions:

• The proposed framework effectively models and simulates diverse crowd behaviors, including collective misbehavior.
• Agent-based modeling with psychological components offers a powerful tool for understanding crowd dynamics.
• This approach advances the computational study of social psychology and crowd behavior.