Agent-Based Modeling¶
Computational methodology that simulates complex systems by modeling individual agents (people, institutions, bots, or other entities) as autonomous actors with defined properties, decision-making rules, and interaction mechanisms. The aggregate behavior that emerges from many agents' interactions can reveal macro-level system dynamics not directly specified at the micro level.
In misinformation research, agent-based models are used to simulate how fake news propagates through populations, how individuals form and update beliefs, and how interventions (fact-checks, warnings, counter-messaging) can slow or reverse the spread of false information.
Key papers¶
- From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake News — LLM-based agents with personality traits and reasoning for opinion dynamics on fake news
- Propagation Models — broader category including agent-based and differential equation approaches
Related topics¶
- Opinion Dynamics — how individual beliefs evolve through interaction and influence
- Fake News Propagation Simulation — application of ABM to misinformation spread
- Personality Traits and Fake News Susceptibility — how individual characteristics affect susceptibility in agent-based simulations