Simulated Social Networks: MOSAIC Explores the Spread and Regulation of Content by AI Agents

The spread of information, particularly in social networks, is increasingly influenced by artificial intelligence. To better understand these complex dynamics and develop strategies for content regulation, especially misinformation, simulation environments are gaining importance. A promising approach is MOSAIC, a new open-source framework for simulating social networks.

MOSAIC (Modeling Social AI for Content Dissemination and Regulation in Multi-Agent Simulations) uses generative language models to simulate the behavior of users in social networks. These AI agents interact within a directed social graph and make decisions about whether to like, share, or report content. What makes MOSAIC special is the detailed modeling of user profiles. By using finely tuned personas, a more realistic simulation of information flow and interaction dynamics is enabled.

A central aspect of MOSAIC is the investigation of disinformation campaigns and the evaluation of various moderation strategies. Initial results show that the implemented strategies can not only curb the spread of misinformation but also positively influence user engagement. This suggests that effective moderation does not necessarily have to lead to a restriction of user activity.

The researchers are also analyzing the distribution paths of popular content within the simulation. An exciting research approach is the investigation of whether the reasons verbalized by the AI agents for their interactions match the actual interaction patterns. This analysis can provide valuable insights into the decision-making processes of the agents and the emergence of trends.

MOSAIC offers a flexible platform for exploring various research questions in the field of social networks and artificial intelligence. By providing the framework as open-source, further research and development in this important area is promoted. Scientists can use MOSAIC to simulate their own scenarios, test different moderation strategies, and investigate the impact of AI on information dissemination.

The combination of generative language models with multi-agent simulations opens up new possibilities for understanding complex social dynamics. MOSAIC makes an important contribution to the research of the interactions between AI and society and offers a valuable tool for the development of strategies for content regulation in the digital world.

The further development of MOSAIC and similar simulation platforms will contribute to better managing the challenges of the information society and harnessing the potential of AI for a positive shaping of social networks.

Bibliography: - https://arxiv.org/abs/2411.16031 - https://www.researchgate.net/publication/386112826_Agent-Based_Modelling_Meets_Generative_AI_in_Social_Network_Simulations - https://cvpr.thecvf.com/Conferences/2025/AcceptedPapers - https://cvpr.thecvf.com/Conferences/2024/AcceptedPapers - https://arxiv.org/pdf/2405.06700 - https://www.researchgate.net/publication/354998329_Multi-agent_modeling_and_simulation_in_the_AI_age - https://github.com/kyegomez/awesome-multi-agent-papers - https://github.com/zhtjtcz/Mine-Arxiv - https://smythos.com/ai-agents/multi-agent-systems/multi-agent-systems-simulation/ - https://arxiv.org/abs/2504.07830