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Eigenvectors of adjacency matrices are useful as measures of centrality or of status. However, they are misapplied to asymmetric networks in which some positions are unchosen. For these networks, an alternative measure of centrality is suggested that equals an eigenvector when eigenvectors can be used and provides meaningfully comparable results when they(More)
Eigenvectors, and the related centrality measure Bonacich's c(β), have advantages over graph-theoretic measures like degree, betweenness, and closeness centrality: they can be used in signed and valued graphs and the beta parameter in c(β) permits the calculation of power measures for a wider variety of types of exchange. Degree, betweenness, and closeness(More)
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We review three decades of research linking social network methods with world systems theory. We identify four themes nested within two versions of a general social network methodology—the identification of network Roles and Position. The themes vary by the type of data and the definition of equivalence used to identify roles and positions. Second, we(More)