On computation of clustering coefficient in a class of random networks
  The random networks enriched with additional structures as metric and group-symmetry in background metric space are investigated. The important quantities like he clustering coefficient as well as the mean degree of separation in such networks are effectively computed with help of additional structures. Representative models are discussed in details. 
Michal Demetrian, Martin Nehez
math.ST stat.TH