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You should not get negative values. This indicates that the value of the
attenuation factor is too large (in absolute size) for the method to
converge. It is often necessary to pick quite small values of the beta
parameter. If your matrix is a reasonable size you can use ucinet matrix
algebra to find the eigenvalues (use the svd command) 


Martin Everett
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University of Westminster
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-----Original Message-----
From: Social Networks Discussion Forum [mailto:[log in to unmask]] On
Behalf Of Haiko Lietz
Sent: 17 April 2006 14:25
To: [log in to unmask]
Subject: Re: Network Measures

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Dear Nick, all:


If you're using UCINET you have a short verbal description of the measure
under "help" where the underlying theoretical work is referenced. You can
retrieve some of it using the JSTOR database. Much was published in "Social
Networks".

My introduction to SNA was also Bob Hanneman's online tutorial:

http://www.faculty.ucr.edu/~hanneman/


This brings me to a follow-up question:

I want to use UCINET's Bonacich power measure (Network > Centrality >
Power). The measure can deliver negative centrality values that I'm not sure
how to interpret.

I've correlated c(alpha,0.1) results with regular degree centrality, and
that tells me that I have to use the absolute values of the results when
dealing with positive beta values.

But do I also have to take the abs val when dealing with negatively
connected networks (negative beta)?


My name is Haiko Lietz. I'm a graduate student at Mittweida University 
of Applied Sciences, Germany. As a freelance reporter I have also 
started applying SNA or Journalistic Network Analysis, as you might call it.


Best wishes

Haiko Lietz

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