Characteristic path length, global and local efficiency, and clustering coefficient of a graph

Version 1.2.0.0 (2.78 KB) by Nathan Cahill
Computes various graph-theoretic properties related to network connectivity
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Updated 30 Aug 2015

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This code implements the graph-theoretic properties discussed in the papers:
A) N.D. Cahill, J. Lind, and D.A. Narayan, "Measuring Brain Connectivity," Bulletin of the Institute of Combinatorics & Its Applications, 69, pp. 68-78, September 2013. (Available online: http://people.rit.edu/ndcsma/pubs/BICA_Sept_2013.pdf)

B) B. Ek, C. VerSchneider, N.D. Cahill, and D.A. Narayan, "A Comprehensive Comparison of Graph Theory Metrics for Social Networks," Social Network Analysis and Mining, 5(1), pp. 1-7, July 2015.

A script is provided that shows how to compute the graph-theoretic properties for the exercises described in these papers.

Cite As

Nathan Cahill (2026). Characteristic path length, global and local efficiency, and clustering coefficient of a graph (https://www.mathworks.com/matlabcentral/fileexchange/46084-characteristic-path-length-global-and-local-efficiency-and-clustering-coefficient-of-a-graph), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2013b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.2.0.0

updated citation
1.1.0.0

Added both closed and open versions of clustering coefficient and local efficiency, and expanded the set of examples in exampleScript.m.
1.0.0.0