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A note on measures of similarity based on centrality

✍ Scribed by Soong Moon Kang

Publisher: Elsevier Science
Year: 2007
Tongue: English
Weight: 694 KB
Volume: 29
Category: Article
ISSN: 0378-8733
DOI: 10.1016/j.socnet.2006.04.004

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✦ Synopsis

This note presents a measure of similarity between connected nodes in terms of centrality based on Euclidean distances, and compares it to 'assortative mixing' [Newman, M.E.J., 2002. Assortative mixing in networks. Physical Review Letters 89, 208701], which is based on Pearson correlation coefficient. This study suggests that the measure based on Euclidean distances may be more appropriate for relatively smaller (N < 500) and denser networks.

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