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On 3/28/06, Srikanth <[log in to unmask]> wrote:
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> I am trying to solve the following problem: I have relationship data
> collected at various points in time regarding the participation of different
> members in a discussion group. Data were accumulated periodically, so the
> network at time T+1 consists of the mapping of all discussions that have
> occurred in the period between T and T+1. The data are in the form of
> adjacency matrices. I need to compare the networks that existed at different
> time periods.
I was just reading an article in Science by Gueorgi Kossinets and his
advisor Duncan Watts that did a longitudinal study of a university
(that I only discovered I had a copy of because of reading the
archives here!). Here's the link:
They had continuous data but most of their techniques should still
apply to you. In fact, it occurs to me that you are probably wrong to
just compare the network at T, T+1... because the network is probably
not discrete like that, but instead each past state has a varying
amount of influence on the present.
You'll want to read the 'supporting online material' if you have
access to it; it has the 'methods' section. Some excerpts:
They define a "sampling period" tau to determine which links are
considered ongoing links, and which are considered broken. In their
study they chose Tau=60 days which they figured out by analyzing the
distribution of communications (95% of responses came within 60 days).
What is your goal in your study? I'm still just learning SNA but I
keep hitting up against that the appropriate technique really really
really depends on the data.
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