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I'd also add the paper:
"A nonparametric view of network models and Newman–Girvan and other
by Peter Bickel and Aiyou Chen in PNAS
They review some statistical issues in community detection, and
construct a framework within various modularites, including
Newman-Girvan, can be compared. They propose an alternative
"likelihood modularity" and show it has good properties.
The various latent space or latent class models may be also of interest
(see, e.g., <http://www.jstatsoft.org/v24/i05/>).
On 1/1/10 7:48 AM, Steve Eichert wrote:
> ***** To join INSNA, visit http://www.insna.org ***** Hello,
> I've been using the Newman Girvan algorithm  to identify communities
> within networks of individuals, however, I've been told by someone who I
> respect greatly that Newman Girvan isn't the best algorithm to use for
> identifying communities when dealing with human networks. So, the
> question I have for the group is: what algorithm would you recommend for
> identifying communities when working with networks of people.
>  http://en.wikipedia.org/wiki/Girvan–Newman_algorithm
> All the best,
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