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***** To join INSNA, visit http://www.insna.org ***** Hi all. As long as I know, and as long as modularity maximisation is the objective, the best algorithm currently available is the one by Blondel et al. It is: . extremely simple and elegant, . extremely fast even on huge graphs, . best in maximising modularity, . suitable for weighted networks, . able to produce multi-level decomposition, . well documented and freely implemented. See http://sites.google.com/site/findcommunities/ for reference and code. All the best, ML On Thu, Dec 31, 2009 at 06:48:41PM -0500, Steve Eichert wrote: > ***** To join INSNA, visit http://www.insna.org ***** > > Hello, > > I've been using the Newman Girvan algorithm [1] 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. > > [1] http://en.wikipedia.org/wiki/Girvan–Newman_algorithm > > All the best, > Steve > > _____________________________________________________________________ > SOCNET is a service of INSNA, the professional association for social > network researchers (http://www.insna.org). To unsubscribe, send > an email message to [log in to unmask] containing the line > UNSUBSCRIBE SOCNET in the body of the message. -- --------------- Matthieu Latapy http://www-rp.lip6.fr/~latapy http://www.complexnetworks.fr ----------------------------- _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.