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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)
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Categories and Subject Descriptors 1. INTRODUCTION Bonacich (1972) suggested that the eigenvector of the largest eigenvalues an adjacency matrix could make a good network centrality measure. Unlike degree, which weights every contact equally, the eigenvector weights ties with others according to their centralities. Eigenvector centrality can also be seen as(More)
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