How does network density spread misinformation?
Misinformation Dissemination: Effects of Network Density in Segregated Communities
December 2, 2024
https://arxiv.org/pdf/2411.19866This paper studies how network structure affects the spread of misinformation, particularly focusing on network density (how connected individuals are) and segregation (separation into groups). It uses a simulation model where individuals can be susceptible, believers of misinformation, or fact-checkers.
Key points for LLM-based multi-agent systems:
- Density breeds belief: Denser networks, even with skeptical agents, accelerate misinformation spread due to increased interactions. This highlights the importance of managing communication flow in multi-agent systems.
- Minority influence: A densely connected minority group can significantly influence the majority's belief, even if the majority is less dense. This suggests potential strategies for targeted interventions in multi-agent systems, even within smaller, tightly-knit sub-groups.
- Agent interaction modeling: The susceptible-believer-fact-checker (SBFC) model used here could be adapted for LLM-based agents, incorporating factors like agent trustworthiness, reasoning abilities, and access to external information. This allows exploring different interaction dynamics within a multi-agent system.
- Network topology design: Understanding how network structure affects information flow is crucial for designing robust and resilient multi-agent systems. Considerations include limiting the influence of highly connected malicious agents or bolstering fact-checking mechanisms within the network.