CIShell Manual : Watts-Strogatz Clustering Coefficient
This page last changed on Jan 12, 2011 by dapolley.
DescriptionPros & ConsThe network to analyze must be undirected, otherwise there are no special constraints. ApplicationsBasic analysis tool, not particular for special disciplines or problems. Implementation DetailsThe algorithm requires two inputs, the file where the edges of the network are listed and the number of points for the binned distribution described below. A first read-in of the inputfile will set the values of the number of nodes and edges of the network. In the second read-in the degree of all nodes is calculated and the edges are stored in an array. Then the clustering coefficients for all nodes are calculated and listed in one of the three output files, together with the corresponding node index. The average of the clustering coefficients is determined and displayed in the NWB console. Usage HintsA simple application of this algorithm could be to calculate the clustering coefficient and its distribution for networks created by the modeling algorithms of the NWB. For instance, the inputfile can be created through the Barabasi-Albert model. LinksAcknowledgementsThe algorithm was implemented and documented by S. Fortunato, integrated by S. Fortunato and W. Huang. For the description we acknowledge Wikipedia. ReferencesWatts, D.J., Strogatz, S.H.(1998) Collective dynamics of 'small-world' networks. Nature 393:440-442. See Also |
![]() |
Document generated by Confluence on May 31, 2011 16:37 |