***** To join INSNA, visit http://www.sfu.ca/~insna/ ***** 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 _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.sfu.ca/~insna/). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.