Answers are grounded in this paper and cite their sources.
The entropy of a hierarchical network topology in an ensemble of sparse random networks, with "hidden variables" associated with its nodes, is the log-likelihood that a given network topology is present in the chosen ensemble. We obtain a general formula for this entropy, which has a clear interpretation in some simple limiting cases. The results provide keys with which to solve the general problem of "fitting" a given network with an appropriate ensemble of random networks.
No takes yet. Share an insight, caveat, or question.
Bianconi et al. (2008) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: