multiplex_page_rank: Calculate Multiplex PageRank

Description Usage Arguments Value Author(s) References Examples

Description

Calculate multiplex PageRank following defination by Halu et al.

Usage

1
multiplex_page_rank(graph, ..., beta = 1, gamma = 1, damping = 0.85)

Arguments

graph

(igraph) The base graph with pagerank and name as vertex attributes.

...

(igraph) Supporter graphs with pagerank and name as vertex attributes.

beta

(numeric) Parameters for adjusting supporter graph PageRank values. For the same nodes, PageRank values from different supporter graphs will first be multiplicated. The products will then be exponentiate by beta and gamma, as outgoing edge weights and personalizations of the base graph. Four special multiplex PageRank forms are defined by varying (beta, gamma), including additive (0, 1), multiplicative (1, 0), combined (1, 1) and neutral (0, 0).

gamma

(numeric) Parameters for adjusting supporter graph PageRank values. For the same nodes, PageRank values from different supporter graphs will first be multiplicated. The products will then be exponentiate by beta and gamma, as outgoing edge weights and personalizations of the base graph. Four special multiplex PageRank forms are defined by varying (beta, gamma), including additive (0, 1), multiplicative (1, 0), combined (1, 1) and neutral (0, 0).

damping

(numeric) Damping factor.

Value

(numeric) Multiplex PageRank values.

Author(s)

DING, HONGXU (hd2326@columbia.edu)

References

Halu, Arda, et al. "Multiplex pagerank." PloS one 8.10 (2013).

Examples

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library(igraph)
set.seed(1)
graph1 <- igraph::erdos.renyi.game(100, 0.01, directed = TRUE)
igraph::V(graph1)$name <- 1:100
igraph::V(graph1)$pagerank <- igraph::page_rank(graph1)$vector
set.seed(2)
graph2 <- igraph::erdos.renyi.game(100, 0.01, directed = TRUE)
igraph::V(graph2)$name <- 1:100
igraph::V(graph2)$pagerank <- igraph::page_rank(graph2)$vector
multiplex_page_rank(graph1, graph2)

hd2326/pageRank documentation built on Dec. 18, 2020, 8:44 a.m.