This project aims to develop a simulation tool to model the information ecosystem, specifically how content spreads and is consumed by people in a network. By using agent-based modeling techniques, the project incorporates various features of information flow, network structures, and agent characteristics. The primary benefit of this research is to understand how information propagates and how that propagation may be influenced by various characteristics of agents or network properties. The research also evaluates the effectiveness of different interventions, making it a valuable investment to support a more informed ecosystem. The simulation infrastructure provides a scalable and empirically grounded model to predict the outcomes of individual actions at a larger scale. The research addresses critical issues such as the impact of network dynamics and the consequences of various dynamics. By balancing abstraction with ecological validity, the simulation infrastructure aims to produce realistic and interpretable predictions. The project also explores the trade-offs between accuracy, scalability, and robustness. This comprehensive approach informs better understanding of intervention strategies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.