# LinkRankCentrality

LinkRankCentrality[g,α]

gives the link-rank centralities for edges in the graph g and weight α.

LinkRankCentrality[g,α,β]

gives the link-rank centralities, using weight α and initial vertex page-rank centralities β.

LinkRankCentrality[{vw,},]

uses rules vw to specify the graph g.

# Details and Options • Link-rank centralities represent the likelihood that a person randomly follows a particular link on the web graph.
• Link rank is a way of measuring the importance of links between vertices.
• The link-rank centrality of an edge is the page-rank centrality of its source vertex, divided by its out-degree.
• If β is a scalar, it is taken to mean {β,β,}.
• LinkRankCentrality[g,α] is equivalent to LinkRankCentrality[g,α,1/VertexCount[g]].
• Link-rank centralities are normalized.
• The option can be used to control the precision used in internal computations.
• LinkRankCentrality works with undirected graphs, directed graphs, multigraphs, and mixed graphs.

# Examples

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## Basic Examples(2)

Compute link-rank centralities:

 In:= In:= Out= Highlight:

 In:= In:= Out= Find the probability that a random surfer follows that link:

 In:= In:= Out= Rank web links, with the most visible links first:

 In:= Out//Short= ## Properties & Relations(2)

Introduced in 2014
(10.0)
|
Updated in 2015
(10.3)