Network Formation

Network formation research focuses on understanding how connections arise and evolve in various systems, from social networks to technological infrastructure. Current efforts concentrate on developing realistic network generation models, employing techniques like graph neural networks and large language models, while addressing challenges such as bias and privacy. These advancements are crucial for improving simulations in diverse fields, including epidemiology and social science, and for enabling responsible data sharing by creating realistic yet private synthetic networks. The development of efficient algorithms for learning network structures from data, including partial rankings, is also a key area of ongoing investigation.