MeanClusteringCoefficient
gives the mean clustering coefficient of the graph g.
MeanClusteringCoefficient[{vw,…}]
uses rules vw to specify the graph g.
Details
- MeanClusteringCoefficient is also known as the average or overall clustering coefficient.
- The mean clustering coefficient of g is the mean over all local clustering coefficients of vertices of g.
- MeanClusteringCoefficient works with undirected graphs, directed graphs, and multigraphs.
Examples
open allclose allBasic Examples (2)
Scope (5)
MeanClusteringCoefficient works with undirected graphs:
Use rules to specify the graph:
MeanClusteringCoefficient works with large graphs:
Applications (2)
Properties & Relations (7)
MeanClusteringCoefficient is the mean over all local clustering coefficients of vertices:
The mean clustering coefficient is between 0 and 1:
For a graph with no vertices of degree greater than 1, the mean clustering coefficient is 0:
The mean clustering coefficient of a complete graph with at least three vertices is 1:
Distribution of mean clustering coefficient in BernoulliGraphDistribution:
Distribution of mean clustering coefficient in WattsStrogatzGraphDistribution:
With low rewiring probability and high mean vertex degree, the expected value is near :
With high rewiring probability, the expected value is near 0:
Distribution of mean clustering coefficient in BarabasiAlbertGraphDistribution:
Compare with GlobalClusteringCoefficient:
Text
Wolfram Research (2012), MeanClusteringCoefficient, Wolfram Language function, https://reference.wolfram.com/language/ref/MeanClusteringCoefficient.html (updated 2015).
CMS
Wolfram Language. 2012. "MeanClusteringCoefficient." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2015. https://reference.wolfram.com/language/ref/MeanClusteringCoefficient.html.
APA
Wolfram Language. (2012). MeanClusteringCoefficient. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/MeanClusteringCoefficient.html