Hi Gábor,
thanks for your answer. I was actually asking if such a method was already implemented in igraph (because I'm lazy and didn't want to use a different tool if it was the case). I was considering sampling a limited number of pairs of nodes, using shortest.paths() to process the distance between them, and averaging them, as an estimation. What do you thing of this approach?
The link you propose is interesting, but not all my networks are clearly scale-free. I had found other related works, too. I haven't checked the associated tools yet, but I list them here anyway, since they might interest other igraph users:
- "Fast Shortest Path Distance Estimation in Large Networks", Potamias et al. 2009.
- "Orion: Shortest Path Estimation for Large Social Graphs", Zhao et al. 2010.
- "Fast Fully Dynamic Landmark-based Estimation of Shortest Path Distances in Very Large Graphs", Tretyakov et al. 2011.
source code: couldn't find any
Best,
Vincent