I have a large bipartite network with ~10^4 vertices of type I and ~10^6 vertices of type II. I fitted a nested blockmodel, hoping to identify communities of type I. Unfortunately, the detected communities (at the lowest level in the hierarchy) have a median size that is about twice as big as the empirical evidence suggests; (kind of reminding me of the resolution limit problem).
Is there a way to tune the sizes of the communities at the lowest level? I'm thinking
- could forcing an extra hierarchy level help, or
- adding in another (non-nested) simple block model at the lowest level?
- Is it possible to reduce the penalty on the description length?
Any ideas would be greatly appreciated... many thanks in advance!
Dr Peter Straka
Research Fellow (DECRA)
School of Physical Engineering and Mathematical Sciences | UNSW Canberra