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Algorithm::SocialNetwork 0.07

  Date Added: July 09, 2010  |  Visits: 886


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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 [1]. 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 [1], 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
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License: Freeware Size: 9.22 KB
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