  We provide a method to deduce the preferences governing the restructuring
dynamics of a network from the observed rewiring of the edges. Our approach is
applicable for systems in which the preferences can be formulated in terms of a
single-vertex energy function with f(k) being the contribution of a node of
degree k to the total energy, and the dynamics obeys the detailed balance. The
method is first tested by Monte-Carlo simulations of restructuring graphs with
known energies, then it is used to study variations of real network systems
ranging from the co-authorship network of scientific publications to the asset
graphs of the New York Stock Exchange. The empirical energies obtained from the
restructuring can be described by a universal function f(k) -k ln(k), which is
consistent with and justifies the validity of the preferential attachment rule
proposed for growing networks.
