Characteristic path length, global and local efficiency, and clustering coefficient of a graph
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 (2024). 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 .
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- Sciences > Physics > Networks >
- MATLAB > Mathematics > Graph and Network Algorithms > Construction >
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