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Subject: Re: [UCINET] friendship groups
From: Steve Borgatti <[log in to unmask]>
Reply-To:[log in to unmask]
Date:Mon, 5 Apr 2004 16:42:33 -0400
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*****  To join INSNA, visit http://www.sfu.ca/~insna/  *****

One way to look at clustering methods is as models of group structure.
Classifying actors into mutually exclusive groups (i.e., imposing a
partition) can yield a pretty distorted view of the network -- that is,
be a bad model. Which is why one wants a measure of fit. Even if the fit
is not perfect has the advantage of simplicity. It is, in the words of
Levi-Strauss, "good to think with". As long as we remember that it is a
model, not reality.



I think clustering methods (whether they produce partitions or
overlapping groups) are easily justified as ways to produce simplified
models of the structure (i.e. data reduction), but it requires something
of a leap of a faith to see them as revealing emically defined groups,
by which I mean groups that the actors themselves believe to exist and
identify themselves as members of. [I apologize in advance for that last
sentence]



My $0.02



Steve.









> -----Original Message-----

> From: Social Networks Discussion Forum [mailto:[log in to unmask]]

> On Behalf Of Valdis Krebs

> Sent: Monday, April 05, 2004 2:33 PM

> To: [log in to unmask]

> Subject: Re: [UCINET] friendship groups

>

> *****  To join INSNA, visit http://www.sfu.ca/~insna/  *****

>

> Of all of the social networks I have looked at, I can not remember a

> single one where everyone fell into one and only one group/cluster.

> You will find 'clean components' if you are looking at a *prescribed*

> network such as a department structure in an organization or a class

> structure in a school but NOT with most *emergent* networks.

>

> Are you interested in how the network influences individual behavior?


> If so, I would look at the network neighborhood each individual is

> embedded in.

>

> If you are just looking to discover emergent friendship clusters in

> the overall network, I would apply Mark Newman's recent edge

> betweenness algorithm

>

> _____________________________________________________________________

> SOCNET is a service of INSNA, the professional association for social

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Steve Borgatti

Organization Studies Dept

Boston College

Fax: 978 456 7373

Tel: 617 552 0450

E-mail: [log in to unmask]

_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
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