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Module Version: 0.07

# NAME

`  Algorithm::SocialNetwork - Social Network Analysis`

# SYNOPSIS

```    use Graph::Undirected;
use Algorithm::SocialNetwork;

my \$G = Graph::Undirected->new();
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 vertice's 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 it's 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.