Network Effect

Network effects describe how the value or utility of a system or product increases with the number of users or participants. Current research focuses on understanding and leveraging these effects in diverse contexts, including social networks (analyzing causal impacts and mitigating misinformation), cyber-physical systems (modeling network latency's influence on control systems), and machine learning (optimizing federated learning participation and incentivizing collaboration). This research is significant because it provides tools for analyzing complex interactions within networks, leading to improved model design, more effective interventions, and a deeper understanding of system behavior across various domains.

Papers