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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