I am studying the evolution of weighted and undirected networks over time. I have managed to create a list of networks and to compute different centrality measures stored as node attributes, but I don't know how to extract those to study them in more depth.
Here is a small sample of my data:
el_cc <- data.frame(from = c("BEL", "LUX", "FRN", "UKG","BEL", "LUX", "FRN", "UKG"),
to = c("FRN", "UKG", "DEN", "CND","FRN", "UKG", "DEN", "CND"),
weight = c(1,2,3,4,5,6,7,8),
year = c(2010,2010,2010,2010,2011,2011,2011,2011))
To prepare the data and create the graphs, I run
cc <- split(el_cc, el_cc$year)
get.graphs <- function(data){
# Select columns
data[(names(data) %in% c("from", "to", "weight"))]
# Remove duplicate dyads
data <- data %>%
rowwise() %>%
mutate(tmp = paste(sort(c(from,to)), collapse = ''))
data <- data[!duplicated(data$tmp),]
data$tmp <- NULL
# Create graph
g <- graph_from_data_frame(data, directed = FALSE)
# Degree centrality
g$degreecent <- degree(g, mode="total", normalized = TRUE)
# Betweenness centrality
g$betweenness <- betweenness(g, v = V(g), directed = FALSE, nobigint = TRUE, normalized = TRUE)
# k-core
g$kcore <- coreness(g, mode="all")
return(g)
}
graph.cc <- lapply(cc, get.graphs)
If I try to view elements of graph.cc, I get an error
Error in adjacent_vertices(x, i, mode = if (directed) "out" else "all") :
At iterators.c:763 : Cannot create iterator, invalid vertex id, Invalid vertex id
Error in adjacent_vertices(x, i, mode = if (directed) "out" else "all") :
At iterators.c:763 : Cannot create iterator, invalid vertex id, Invalid vertex id
But if I run the line below, it seems to be fine.
graph.cc$`2011`
But then, from here, I don't know how to access the centrality measures I computed. I have seen plenty of tutorials that show how to use the attributes to plot the network, but I would like to store them in a dataframe for instance or in a list of dataframes. If I was not using a list but if I was working one year at the time, here is what I would do:
# For one year at a time
degreecent <- degree(g, mode="total", normalized = TRUE)
betweenness <- betweenness(g, v = V(g), directed = FALSE, nobigint = TRUE, normalized = TRUE)
kcore <- coreness(g, mode="all")
Centrality_Measures <- data.frame(degreecent, betweenness , kcore , stringsAsFactors=FALSE)
Ideally, I would like to build on this to obtain a list of dataframe with the centrality measures for all nodes over the years. Many thanks in advance!
You cannot see the graphs because graph.cc is not a graph it's a list.
To create a data.frame with the centrality measures wrap the code that works in the single case as a function and lapply it to the graphs' list.
suppressPackageStartupMessages({
library(igraph)
library(dplyr)
})
centrality_measures <- function(g) {
degreecent <- degree(g, mode="total", normalized = TRUE)
betweenness <- betweenness(g, v = V(g), directed = FALSE, normalized = TRUE)
kcore <- coreness(g, mode="all")
Centrality_Measures <- data.frame(degreecent, betweenness, kcore, stringsAsFactors=FALSE)
Centrality_Measures
}
lapply(graph.cc, centrality_measures)
#> $`2010`
#> degreecent betweenness kcore
#> BEL 0.2 0.0 1
#> LUX 0.2 0.0 1
#> FRN 0.4 0.1 1
#> UKG 0.4 0.1 1
#> DEN 0.2 0.0 1
#> CND 0.2 0.0 1
#>
#> $`2011`
#> degreecent betweenness kcore
#> BEL 0.2 0.0 1
#> LUX 0.2 0.0 1
#> FRN 0.4 0.1 1
#> UKG 0.4 0.1 1
#> DEN 0.2 0.0 1
#> CND 0.2 0.0 1
Created on 2022-07-26 by the reprex package (v2.0.1)