XXIV International Sunbelt Social Network ConferencePortorož, Slovenia, May 12 - 16, 2004
Longitudinal social network data are understood in this workshop
as two or more repeated observations of a directed graph on a given node
set (usually between 30 and 100 nodes, sometimes up to a few hundreds).
In other words, this workshop
is about statistical modeling of the dynamics of complete networks. The
workshop teaches the statistical method to analyze such data, as described
in Sociological Methodology - 2001, p. 361-395,
and implemented in the SIENA program.
The statistical model used for
the network evolution allows various network effects (reciprocity,
transitivity, cycles, popularity, etc.), effects of individual
covariates (covariates connected to the sender, the receiver, or the
similarity between sender and receiver), and of dyadic covariates.
One interpretation of this model is an actor-oriented model where
the nodes are actors whose choices determine the network evolution.
Further information about this method, including references and a JAVA
demo, can be found at website
http://stat.gamma.rug.nl/snijders/siena.html. The statistical analysis is
based on Monte Carlo simulations of the network evolution model and
therefore is a bit time-consuming.