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Carl,

In general, I would say this is not a good idea. There are exceptions, but
even then interpretation is tricky since no actual ties have been observed
between the actors. Usually, you must assume that a tie of this type implies
the potential for a real tie. So, for example, if we have a large group of
people that are working together in small teams, and we have a categorical
attribute TEAM which identifies the team for each person, then we can
construct a dyadic variable called SAMETEAM in which ST(i,j) = 1 if T(i) =
T(j) and 0 otherwise. This variable has some merit, particularly if used,
for example, as a control in a dyadic regression. It can be interpreted as
indicating a potential for communication/acquaintanceship between i and j.
Note that if the teams get large (suppose they are prisons or organizations)
then the argument that a sameorg tie implies a social tie gets weak. I think
that the Taylor variable has much less to recommend it than the sameteam or
samegender or samecountryclub variable.

NOte also that "networks" constructed from node attributes have
characteristics that are artifactual. The sameteam variable is an
equivalence relation (it is reflexive, symmetric, transitive). The Taylor
variable O(i)*O(j) will have a core/periphery structure (in the ordinary
sens)e that is based on number of offices if the variance of O is high
enough. So that if city i and city j both have lots and lots of offices,
there will be strong "tie" between them (and both will be in the core). If
city i has many offices but city j does not, there will be a middling tie,
and both have few offices, there will be weak tie (they belong to the
periphery). So you would not want to analyze the structure of this matrix
and then "discover" that it has a core/periphery structure no doubt created
by imperialist capitalist nations who control the tncs, etc.

steve.

----- Original Message -----
From: "Carl Nordlund" <[log in to unmask]>
To: <[log in to unmask]>
Sent: Monday, October 14, 2002 7:08 AM
Subject: Structural data based on actor attributes


> *****  To join INSNA, visit http://www.sfu.ca/~insna/  *****
>
> Dear all,
>
> When studying the 'World City Network', Peter Taylor has specified a
> technique for obtaining structural data which is based on actor attributes
> (Research bulletin 23, GaWC, also published in Geographical Analysis
33(2),
> 2001). He uses a formula like this one:
>
> C(i,j) = O(i) * O(j)
>
> ...where C(i,j) is the total connectivity between actor i and j and where
> O(i) and O(j) are total number of TNC offices of actor i respectively j.
>
> In short, what is done here is an estimation of the structural value
between
> dyads based on internal attributes of the actors. If city i has 2 offices
> and city j has 3 offices, the structural connectivity value between i and
j
> is set to 6, thus implying the total number of links between these two
> actors.
>
> Is this a common way of fetching structural data, i.e to use actor
> attributes like this? Intuitively, what regards Taylor's study, it feels
> like a reasonable good approximation of the structural data but when it is
> only based on actor-internal attributes, I also get the feeling that it
> isn't following a very 'networkish' style!
>
> Yours,
> Carl
> -----
> Carl Nordlund, BA, PhD student
> carl.nordlund(at)humecol.lu.se
> Human Ecology Division
> www.humecol.lu.se
>
> _____________________________________________________________________
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