The static and dynamic analysis of network data using information theory

Abstract Information theory provides us with methods for both the static and dynamic analysis of network data. Since the models are derived within one framework, the results of the multivariate analysis and the time-series analysis can be made relevant for one another. Additionally, using the static model, one can create an exact dendrogram, and determine the precise number of clusters. The algorithm is generalizable to clique analysis. Using the dynamic model, developments can be revealed which were not suggested by the comparison of results of various forms of multivariate analysis for each year separately. The question of using these methods to design research about structure/action relations is discussed.

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