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There are two issues here: one is failure to give credit where it's due
and the other is the actual validity of the work.  I'm just finishing up
a lengthy review article on recent work on networks by mathematicians
and physicists, and although I thought I knew this literature quite well
before I started, I have learned a lot by reading up for the review.  I
agree completely that people have in some cases failed to give credit
for earlier innovations, and this is bad.  But it would be a mistake to
dismiss this work out of hand.  There is a great deal there that would
be of interest to all of us.

In particular response to Mark Handcock's post about "scale-free
networks", I think it would certainly be a mistake to claim that the
physics models, like the "preferential attachment" models, are complete
models of the structure of networks.  Of course there are many different
processes going on in network formation, most of which are absent from
these models.  Therefore, if one compares these simple models to
sociometric data, it's virtually certain they won't match up, and Mark's
work demonstrates this elegantly.  This however doesn't make the models
useless.  There's much to be learned from them, even if they are
incomplete (or maybe even plain wrong).  At the very least, they've
stirred up a whole new community to get interested in network ideas, and
surely that can't be all bad.

Mark Newman.

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