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In the analysis of bibliometric networks, researchers often use mapping andclustering techniques in a combined fashion. Typically, however, mapping andclustering techniques that are used together rely on very different ideas andassumptions. We propose a unified approach to mapping and clustering ofbibliometric networks. We show that the VOS mapping technique and a weightedand parameterized variant of modularity-based clustering can both be derivedfrom the same underlying principle. We illustrate our proposed approach byproducing a combined mapping and clustering of the most frequently citedpublications that appeared in the field of information science in the period1999-2008.

A unified approach to mapping and clustering of bibliometric networks