I am fairly new to igraph in R and to clustering/partitioning algorithms in general.
I have a general question on clusters. My idea is to build a contiguous cluster from a (directed) graph based on an attribute. What I try to achieve is something very similar to https://www.sixhat.net/finding-communities-in-networks-with-r-and-igraph.html. However, I am not sure I understand the functions (e.g. cluster_walktrap()) correctly. (I know there are some clustering methods that work on directed graphs, and some that don't.)
As an example: I use the network net from http://kateto.net/networks-r-igraph. Assuming I would like to end up with contiguous clusters based on the attribute audience.size (contrary to a clustering based on the betweeness), how would I use a clustering function from igraph?
cluster_walktrap(net, weights = E(net)$audience.size, steps = 4)? How do I interpret the weight in this case?
MWE with data from: http://www.kateto.net/wordpress/wp-content/uploads/2016/01/netscix2016.zip
library(igraph)
nodes <- read.csv("Dataset1-Media-Example-NODES.csv", header=T, as.is=T)
links <- read.csv("Dataset1-Media-Example-EDGES.csv", header=T, as.is=T)
net <- graph_from_data_frame(d=links, vertices=nodes, directed=T)
net <- simplify(net, remove.multiple = F, remove.loops = T)
cluster_walktrap(net, weights = E(net)$audience.size, steps = 4)
Thank you very much!
