Network Centrality Plot
plotNetCentrality.RdCreates a bar plot with key network centrality measures.
Usage
plotNetCentrality(g,
title="Network Centrality Measures",
subtitle="Ranking of nodes according to centrality.",
caption="Source: Own elaboration.",
palette=c("#1B9E77",
"#D95F02",
"#7570B3",
"#E7298A",
"#66A61E",
"#E6AB02",
"#A6761D",
"#666666"),
methods=c("degree",
"authority",
"page_rank",
"eigenvector",
"betweenness",
"closeness",
"hub"),
topn=20,
ties.method="min")Arguments
- g
An igraph object.
- title
A character string. The title of the chart. The default is "Network Centrality Measures".
- subtitle
A character string. The subtitle of the chart. The default is "Ranking of nodes according to centrality.".
- caption
A character string. The caption of the chart. The default is "Source: Own elaboration.".
- palette
A character vector. The color palette to be used in the chart.
- methods
A character vector. The network centrality measures to be used in the chart. The default is c("degree", "authority", "page_rank", "eigenvector", "betweenness", "closeness", "hub").
- topn
An integer. The number of top nodes to be displayed in the chart. The default is 20.
- ties.method
A character string. The method to break ties in the ranking. The default is "min".
Details
The function corNet generates a network graph (sociogram) for the correlation among words in a corpus. The default centrality measures are: degree, authority, page rank, eigenvector, betweenness, closeness and hub.
Examples
if (FALSE) {
# Create a random network graph
library(igraph)
g <- sample_gnp(100, 1/100)
# Plot the network centrality measures
plotNetCentrality(g)
}