Coarse-graining the dynamics of network evolution: the rise and fall of   a networked society
  We explore a systematic approach to studying the dynamics of evolving networks at a coarse-grained, system level. We emphasize the importance of finding good observables (network properties) in terms of which coarse grained models can be developed. We illustrate our approach through a particular social network model: the "rise and fall" of a networked society [1]: we implement our low-dimensional description computationally using the equation-free approach and show how it can be used to (a) accelerate simulations and (b) extract system-level stability/bifurcation information from the detailed dynamic model. We discuss other system-level tasks that can be enabled through such a computer-assisted coarse graining approach. 
Andreas C. Tsoumanis, Karthikeyan Rajendran, Constantinos I. Siettos   and Ioannis G. Kevrekidis
physics.soc-ph cond-mat.stat-mech physics.comp-ph