CONCEPT
Network Science
Network science emerged in the late 1990s from the recognition that systems as different as the web, metabolic networks, scientific citations, airline routes, and friendships shared measurable structural properties — scale-free degree distributions, small-world path lengths, community structure, and characteristic dynamics of information spreading, failure propagation, and growth. The field synthesizes tools from graph theory, statistical physics, sociology, and computer science. Barabási's Center for Complex Network Research at Northeastern is among its intellectual centers. Applied to AI, network science offers a rigorous vocabulary for describing what 'democratization' and 'concentration' and 'disruption' actually mean at the structural level.
In The You On AI Field Guide
Before network science, the study of networks was fragmented. Sociologists had social network analysis, going back to Moreno's sociograms in the 1930s. Graph theorists had Erdős-Rényi random graphs. Physicists had percolation and critical phenomena. Computer scientists had internet topology and distributed systems. These communities rarely talked to each other, and the accumulated empirical patterns — that real