library(igraph)
source("http://michael.hahsler.net/SMU/ScientificCompR/code/map.R")
# 1->2; 1->3, 2->1, 3->4, 4->3
g <- graph.formula(1 -+ 2, 1 -+ 3, 2 -+ 1, 3 -+ 4, 4 -+ 3)
plot(g)
# Normal PageRank
page.rank(g, damping=0.70)$vector
# Topic-specific PageRank (assume node '1' and '2' are interesting topic)
page.rank(g, damping=0.70, personalized=c(1/2, 1/2, 0, 0))$vector
# Topic-specific PageRank with weight (node '1' weight 2 when node '2' weight 1)
page.rank(g, damping=0.70, personalized=c(2/3, 1/3, 0, 0))$vector
More info:
http://michael.hahsler.net/SMU/LearnROnYourOwn/code/igraph.html
http://stats.stackexchange.com/questions/175517/calculating-personalized-pagerank-in-r
