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hi folks,
   I'm working with some "dynamic" network data on classroom
interactions collected by Dan McFarland.  One of the things we are
interested in looking at is some measure of "stability" or "repeating
patterns" in interaction networks over time.

There are of course all sorts of interesting theoretical questions in
how (or if) one ought to aggregate dyads to create networks.  But
assuming that one has a series of matrices describing network change
over time, is it possible to generate a "stability statistic" without
an explicit model of the underlying network processes?  (stable in
the sense of repeating relations and sequences, rather than the sense
of "fragility" or susceptibility to perturbations - 'tho they may be
linked)  Simple correlations of successive networks seems not to be
so effective as it is very sensitive timescale of the patterns one is
looking for, and sociomatrices tend to be very sparse and zero
dominated.

   If anyone has experience/thoughts/references on this topic I'd
greatly appreciate hearing about them, and will of course compile and
resubmit refs,

   thanks,
  -skye

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