There are several including work by Guimera , Newman-Girvan, Factions in UCINET.


Mine (KliqueFinder) is explicitly based on a block model/ERGM framework.


Frank. K.A. 1995. Identifying Cohesive Subgroups. Social Networks (17): 27-56


(Snijders & Nowicki also cluster explicitly on a block-model framework).


Mine includes

1)      Monte carlo test of statistical significance for the clusters identified

2)      Batch mode for multiple applications

3)      Two-mode extension

a.       *Field, S. *Frank, K.A., Schiller, K, Riegle-Crumb, C, and Muller, C. (2006). "Identifying Social Contexts in Affiliation Networks: Preserving the Duality of People and Events.  Social Networks 28:97-123. * coequal first authorship

4)      coupled with Netdraw KliqueFinder makes visualizations



Generally, see:




The interface is easier than it used to be – see the ppt above.





Ken Frank

MSU Foundation Professor of Sociometrics

Measurement and Quantitative Methods

Counseling, Educational Psychology and Special Education


Professor of Fisheries and Wildlife

Room 462 Erickson Hall

620 Farm Lane

Michigan State University

East Lansing, MI 48824-1034 phone: 517-355-9567 fax: 517-353-6393 [log in to unmask]


From: Social Networks Discussion Forum [mailto:[log in to unmask]] On Behalf Of Muhammad Qasim Pasta
Sent: Tuesday, November 08, 2016 7:53 AM
To: [log in to unmask]
Subject: Community detection algorithms for non-overlapping community based on stochastic block models


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Can you refer me any available implementation of community detection algorithms based on stochastic block models for detection of non-overlapping communities?


Thanks in advance,

Muhammad Qasim Pasta

Cell: +92-333-3158277


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