**A17. Barnett,
G. & Rice, R.E. (1985). Longitudinal non-Euclidean networks:
Applying
Galileo. ***Social Networks*, *7*(4), 287-322.

**This article discusses the theoretical utility of using a
non-Euclidean
spatial manifold when describing social networks. It proposes that a
variant
of metric MDS, the Galileo System, can be particularly useful in
analyzing
social networks and their changes over time, partially because it does
not impose Euclidean assumptions on the data. Two sets of longitudinal
network data are examined with Galileo. One is the American air traffic
network from 1968-81. The other is ten groups engaged in a computer
conference
over a 24 month period. In both cases, the results indicate that a
Riemannian
spatial manifold is required to describe the network structure.
Consistent
theoretically valid results based upon the non-Euclidean components of
spatial manifold are obtained. Further, they could be readily explained
by exogenous factors. The implications of these results for network
analysis
are discussed.**
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