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.

Details and OptionsDetails 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 .
  • LinkRankCentrality[g,α] is equivalent to LinkRankCentrality[g,α,1/VertexCount[g]].
  • Link-rank centralities are normalized.
  • The option WorkingPrecision->p can be used to control the precision used in internal computations.
  • LinkRankCentrality works with undirected graphs, directed graphs, multigraphs, and mixed graphs.

ExamplesExamplesopen allclose all

Basic Examples  (2)Basic Examples  (2)

Compute link-rank centralities:

In[1]:=
Click for copyable input
In[2]:=
Click for copyable input
Out[2]=

Highlight:

In[3]:=
Click for copyable input
In[4]:=
Click for copyable input
Out[4]=

Find the probability that a random surfer follows that link:

In[1]:=
Click for copyable input
In[2]:=
Click for copyable input
Out[2]=

Rank web links, with the most visible links first:

In[3]:=
Click for copyable input
Out[3]//Short=
Introduced in 2014
(10.0)