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Social Network Analysis and Mining

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01-12-2015 | Original Article

A comprehensive comparison of graph theory metrics for social networks

Authors: Bryan Ek, Caitlin VerSchneider, Nathan D. Cahill, Darren A. Narayan

Published in: Social Network Analysis and Mining | Issue 1/2015

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Abstract

In this paper, we explore the relationship between two metrics that appear in the literature of social networks, local efficiency and the clustering coefficients. Next, we investigate these properties for a selection of real-world networks involving fMRI data from athletes and show for non-sparse graphs the relationship between the two properties is very close to linear.

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Title: A comprehensive comparison of graph theory metrics for social networks
Authors: Bryan Ek
Caitlin VerSchneider
Nathan D. Cahill
Darren A. Narayan
Publication date: 01-12-2015
Publisher: Springer Vienna
Published in: Social Network Analysis and Mining / Issue 1/2015
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-015-0272-2

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