centrality_pagerank: PageRank Centrality

In cograph: Analysis and Visualization of Complex Networks

PageRank Centrality

Description

Random walk centrality measuring node importance. Simulates a random walker that follows edges with probability damping and jumps to a random node with probability 1 - damping.

Usage

centrality_pagerank(x, damping = 0.85, personalized = NULL, ...)

Arguments

x	Network input (matrix, igraph, network, cograph_network, tna object).
damping	Damping factor (probability of following an edge). Default 0.85.
personalized	Named numeric vector for personalized PageRank. Values should sum to 1. Default NULL (uniform).
...	Additional arguments passed to centrality (e.g., weighted, directed).

Value

Named numeric vector of PageRank values.

See Also

centrality for computing multiple measures at once, centrality_eigenvector for a related measure.

Examples

adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), 3, 3)
rownames(adj) <- colnames(adj) <- c("A", "B", "C")
centrality_pagerank(adj)
centrality_pagerank(adj, damping = 0.9)

cograph documentation built on April 1, 2026, 1:07 a.m.