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Dear List,

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.

Best regards,
Simone

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