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Date Added: July 09, 2010  |  Visits: 886 Report Broken Link Printer Friendly Version Product Homepage Download (96 downloads)

Algorithm::SocialNetwork is a social network analysis. SYNOPSIS use Graph::Undirected; use Algorithm::SocialNetwork; my \$G = Graph::Undirected->new(); \$G->add_edges([qw(a b)], [qw(b c)]); my \$algo = Algorithm::SocialNetwork->new(graph => \$G3); my \$BC = \$algo->BetweenessCentrality(); # \$BC->{a} is 0 # \$BC->{b} is 2 # \$BC->{c} is 0 METHODS So far this module implement the algorithm provided in . More handy algorithm would be included in the future. This module is a Spiffy module, methods provided as "field" are marked. new([graph => \$G]) Object constructor, an optional graph parameter could be passed in to specify the network graph to be analyzed. graph([\$G]) [Spiffy field] Without arguments, this method return the current Graph object. BetweenessCentrality([\$vertex]) The implementation of algorithm provided in , if an optional parameter \$vertex is given, return the BetwenessCentrality value of that vertex, otherwise, return all vertices BetweenessCentrality value, stored in a hash, which hash node name as keys. ClusteringCoefficient(\$vertex) Return the clustering coefficient of a given vertex. WeightedClusteringCoefficient(\$vertex) Return the weighted clustering coefficient of a given vertex. The graph object passed in should have weight attribute set on edges. Weights are default to 1 if its not set. DistanceCentrality(\$vertex) Return the distance centrality of a given vertex. ClosenessCentrality(\$vertex) An alias of DistanceCentrality(). GraphCentrality(\$vertex) Return the graph centrality of a given vertex. edges(@vertices) Return a list of edges that connets any two of @vertices..

 Requirements: No special requirements Platforms: Linux Keyword: Algorithmsocialnetwork,  Bc,  Betweenesscentrality,  Edges,  Given,  Graph,  Libraries,  Network,  Programming,  Return,  Social Network,  Socialnetwork,  Vertex Users rating: 0/10        