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It depends on what phenomenon you are trying to study. Is it a transmission
process (such as disease or communication), or is it a non-transmission
process (such as friendship)? If it is a transmission process, directed
measures are indicated; if non-transmission, go with symmetric measures.
And if it is a transmission process, who intends the transmission? In an
infection process, no one intends transmission; in coordination, both
intend; in influence, only the sender intends; in support, only the
recipient. So for studying disease or influence, centrality measures (based
on out-degree) measure what you intend; on the other hand, for studying
support, prestige measures (based on in-degree) are appropriate. We discuss
this briefly in
Bell, Atkinson & Carlson (1999) Centrality measures for disease transmission
measures. Social networks 21: 1-21.
Since your data are undirected, you will not be able to measure transmission
unambiguously (although many before you have been undaunted by, unaware of,
or unconcerned by this restriction).
----- Original Message -----
From: "Jorge Colazo" <[log in to unmask]>
To: <[log in to unmask]>
Sent: Wednesday, September 07, 2005 9:07 AM
Subject: Which measures completely describe a network?
> ***** To join INSNA, visit http://www.insna.org *****
> What is the set of measures that can be used in an empirical study to most
> accurately and completely describe a given network?
> For example, the different centrality indices focus on different
> properties and
> concepts (e.g. closure, brokerage, etc.). In addition, and this depending
> on the
> configuration of the network, the measures are naturally correlated
> indicating some
> degree of overlap.
> Is there a conceptual (other than Friedkin 1991 AJS and related work)
> that would allow one to choose a set of measures with minimum overlap and
> comprehensiveness to describe a given network?
> If yes, are there examples of empirical studies using such a group of
> This is a general question, but by the way, in my specific case I am
> dealing with a
> big, undirected, valued network.
> Thank you very much.
> Jorge A. Colazo
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