LISTSERV mailing list manager LISTSERV 16.0

Help for SOCNET Archives


SOCNET Archives

SOCNET Archives


SOCNET@LISTS.UFL.EDU


View:

Message:

[

First

|

Previous

|

Next

|

Last

]

By Topic:

[

First

|

Previous

|

Next

|

Last

]

By Author:

[

First

|

Previous

|

Next

|

Last

]

Font:

Proportional Font

LISTSERV Archives

LISTSERV Archives

SOCNET Home

SOCNET Home

SOCNET  November 2003

SOCNET November 2003

Subject:

Re: Fwd: Clustering Coefficients & 2-Mode Networks

From:

"Baerveldt, dr. C. (Chris)" <[log in to unmask]>

Reply-To:

Baerveldt, dr. C. (Chris)

Date:

Mon, 24 Nov 2003 07:55:12 +0100

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (1 lines)

0/ӯ芯5#@,?i?l/00Can't you use the segmentation indexes, e.g., the ratio of 4-paths to the ratio of 3-paths?
See Baerveldt & Snijders in Social Networks (1994), where we introduced these in social network analysis.
 
cheers,
Chris Baerveldt

	-----Oorspronkelijk bericht----- 
	Van: Social Networks Discussion Forum namens Garry Robins 
	Verzonden: ma 24-11-2003 06:53 
	Aan: [log in to unmask] 
	CC: 
	Onderwerp: Fwd: Clustering Coefficients & 2-Mode Networks
	
	

	*****  To join INSNA, visit http://www.sfu.ca/~insna/  *****
	
	In a forthcoming article in CMOT, Malcolm Alexander and I propose a
	bipartite clustering coefficient in the context of interlocking
	directorates. In a 1-mode graph, one method to measure clustering is the
	ratio of the number of triangles in the graph to the number of
	2-paths.  Our bipartite coefficient is analogous:  it is the ratio of the
	number of  "closed 4-paths" in the bipartite graph to the number of
	3-paths, where a closed 4-path comprises 4 edges on 4-nodes. Of course,
	this bipartite configuration translates as a multiple connection between
	nodes in the 1-mode graphs derived from the bipartite graph.
	
	In 1-mode networks of relatively low density with a fixed number of edges,
	many triangles can only form at the expense of possibly disconnecting the
	network. In other words, localized closure of 2-paths into triangles (high
	clustering) may be at the cost of more global connectivity.  Analogously
	for a bipartite graph, if the bipartite clustering coefficient is high,
	then there is closure of many 3-paths. So for two bipartite graphs with
	similar numbers of edges, we expect the graph with the higher bipartite
	clustering ratio will show lower levels of global connectivity.  In our
	study, we found much higher values than expected of bipartite clustering
	(ie compared to various baseline distributions), indicating that shared
	memberships of different company boards by pairs of directors was a major
	feature of the data, with potential repercussions for connectivity across
	the bipartite system.
	
	cheers,
	
	
	Garry Robins
	
	
	
	
	>Giovanni Roberto Ruffini wrote:
	>
	>I apologize if this is a hopelessly vague question. I am having a rather
	>hard time articulating it, and know that I have tried to do so with some
	>of you unsuccessfully in the past.
	>
	>I am exploring the utility of the concept of clustering coefficients in
	>analyzing the social connections of an ancient Egyptian village. But the
	>connections I am working with are ones I have derived by running an
	>affiliations function on a two-mode network, thus turning indirect
	>connections (person->legal document->second person) into direct ones.
	>
	>I would like to use the (exceptionally high) clustering coefficient of
	>this derived one-mode network to tell me something about the extent to
	>which this village was ordered at the group level, by guild, by
	>peer-group, etc. But it starts to occur to me that I cannot escape the
	>distorting lense of the (now removed) texts linking person 1 to person 2.
	>In other words, isn't the clustering coefficient in this case nothing but
	>a measure of how much the names in each text overlap? So, in that sense,
	>it tells us nothing about the society's structure itself, and everything
	>about the clustering of the evidence for it.
	>
	>Am I understanding this correctly? Should I despair? Or is the clustering
	>coefficient still an interesting number, even in light of this distorting
	>problem? If so, how?
	>
	>I have looked at Watts _JAS_ 1999 fruitfully, although I am alarmed at
	>the prospect of calling my Egyptians connected cavemen! :) What I think I
	>need next is a way to be sure I'm understanding what I've read, and can
	>put it in appropriately concrete (social, textual, methodological) terms.
	>
	>Thanks for your thoughts!
	>
	>Giovanni Ruffini
	
	Dr Garry Robins
	Department of Psychology
	School of Behavioural Science
	The University of Melbourne
	Victoria 3010
	Australia
	
	Tel: 61 3 8344 6372
	Fax: 61 3 9347 6618
	Web: http://www.psych.unimelb.edu.au/staff/robins.html
	
	_____________________________________________________________________
	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.
	

00000000000000000#4Eǫ' ԍ/鮇޲Ȩ?j(r&~"jY޷
+ޱr/?0v/ӯr/zwZj*?,jlz+-(֢)^XyCRPDD#4Eۡ/z

Top of Message | Previous Page | Permalink

Advanced Options


Options

Log In

Log In

Get Password

Get Password


Search Archives

Search Archives


Subscribe or Unsubscribe

Subscribe or Unsubscribe


Archives

September 2019
August 2019
July 2019
June 2019
May 2019
April 2019
March 2019
February 2019
January 2019
December 2018
November 2018
October 2018
September 2018
August 2018
July 2018
June 2018
May 2018
April 2018
March 2018
February 2018
January 2018
December 2017
November 2017
October 2017
September 2017
August 2017
July 2017
June 2017
May 2017
April 2017
March 2017
February 2017
January 2017
December 2016
November 2016
October 2016
September 2016
August 2016
July 2016
June 2016
May 2016
April 2016
March 2016
February 2016
January 2016
December 2015
November 2015
October 2015
September 2015
August 2015
July 2015
June 2015
May 2015
April 2015
March 2015
February 2015
January 2015
December 2014
November 2014
October 2014
September 2014
August 2014
July 2014
June 2014
May 2014
April 2014
March 2014
February 2014
January 2014
December 2013
November 2013
October 2013
September 2013
August 2013
July 2013
June 2013
May 2013
April 2013
March 2013
February 2013
January 2013
December 2012
November 2012
October 2012
September 2012
August 2012
July 2012
June 2012
May 2012
April 2012
March 2012
February 2012
January 2012
December 2011
November 2011
October 2011
September 2011
August 2011
July 2011
June 2011
May 2011
April 2011
March 2011
February 2011
January 2011
December 2010
November 2010
October 2010
September 2010
August 2010
July 2010
June 2010
May 2010
April 2010
March 2010
February 2010
January 2010
December 2009
November 2009
October 2009
September 2009
August 2009
July 2009
June 2009
May 2009
April 2009
March 2009
February 2009
January 2009
December 2008
November 2008
October 2008
September 2008
August 2008
July 2008, Week 62
July 2008
June 2008
May 2008
April 2008
March 2008
February 2008
January 2008
December 2007
November 2007
October 2007
September 2007
August 2007
July 2007
June 2007
May 2007
April 2007
March 2007
February 2007
January 2007
December 2006
November 2006
October 2006
September 2006
August 2006
July 2006
June 2006
May 2006
April 2006
March 2006
February 2006
January 2006
December 2005
November 2005
October 2005
September 2005
August 2005
July 2005
June 2005
May 2005
April 2005
March 2005
February 2005
January 2005
December 2004
November 2004
October 2004
September 2004
August 2004
July 2004
June 2004
May 2004
April 2004
March 2004
February 2004
January 2004
December 2003
November 2003
October 2003
September 2003
August 2003
July 2003
June 2003
May 2003
April 2003
March 2003
February 2003
January 2003
December 2002
November 2002
October 2002
September 2002
August 2002
July 2002
June 2002
May 2002
April 2002
March 2002
February 2002
January 2002
December 2001
November 2001
October 2001
September 2001
August 2001
July 2001
June 2001
May 2001

ATOM RSS1 RSS2



LISTS.UFL.EDU

CataList Email List Search Powered by the LISTSERV Email List Manager