I have an empirical diffusion network, where a node represent an actor and a link between actor A to actor B represent the fact that actor A influenced actor B. I have recorded, for each actor, the time he adopted the innovation.
I am trying to simulate, with different mechanisms, a bunch of diffusion networks that closely approximate the empirical one.
I have many statistics in place already, including GOF measures like degree distribution, ESP distribution and Path length distribution (a la statnet)
All these measures tell me something about the topological proximity between simulated networks and the empirical one. However, I'd like to say something about:
1/ the activation timing of the nodes
2/ if the sequence of activations (who influences whom) realistically mimics the empirical one.
Is there a commonly adopted strategy in this case?
About the activation timing of nodes, I was thinking about some sort of ranking measure. About the second point, I have no clue so far... A simple QAP correlation between empirical and simulated networks would be sufficient?
Any help more than appreciated.