Can LLMs simulate fake news spread?
Large Language Model-driven Multi-Agent Simulation for News Diffusion Under Different Network Structures
October 21, 2024
https://arxiv.org/pdf/2410.13909This research investigates how fake news spreads on social media using a simulated network with LLM-powered agents. It found that an agent's personality (especially extroversion and openness) and the network's structure significantly impact how quickly fake news travels.
The key takeaway for LLM-based multi-agent systems is that:
- Simulating agents with personality traits leads to more realistic news spread patterns.
- Simply encouraging agents to think critically by adding comments isn't effective at stopping fake news.
- Blocking highly connected agents and providing accuracy checks are promising countermeasures, but their effectiveness depends on the network's structure.
- LLM simulations are valuable for understanding how fake news spreads and testing mitigation strategies in a controlled environment.