I’ve plotted several word association graphs for this New York Times article (1st paragraph) using R and the igraph library.
#1, random method
#2, circle method
#3, sphere method
#4, spring method
#5, fruchterman-reingold method
# 6, kamada-kawai method
#7, graphopt method
The red vertices mark cliques. Here’s the (rough) R code for plotting such graphs:
rm(list=ls());
library("igraph");
library("Cairo");
# read parameters
print("Text-as-Graph for R 0.1");
print("------------------------------------");
print("Path (no trailing slash): ");
datafolder <- scan(file="", what="char");
print("Text file: ");
datafile <- scan(file="", what="char");
txt <- scan(paste(datafolder, datafile, sep="/"), what="char", sep="\n", encoding="UTF-8");
print("Width/Height (e.g. 1024x768): ");
res <- scan(file="", what="char");
rwidth <- unlist(strsplit(res, "x"))[1]
rheight <- unlist(strsplit(res, "x"))[2]
words <- unlist(strsplit(gsub("[[:punct:]]", " ", tolower(txt)), "[[:space:]]+"));
g.start <- 1;
g.end <- length(words) - 1;
assocs <- matrix(nrow=g.end, ncol=2)
for (i in g.start:g.end)
{
assocs[i,1] <- words[i];
assocs[i,2] <- words[i+1];
print(paste("Pass #", i, " of ", g.end, ". ", "Node word is ", toupper(words[i]), ".", sep=""));
}
print("Build graph from data frame...");
g.assocs <- graph.data.frame(assocs, directed=F);
print("Label vertices...");
V(g.assocs)$label <- V(g.assocs)$name;
print("Associate colors...");
V(g.assocs)$color <- "Gray";
print("Find cliques...");
V(g.assocs)[unlist(largest.cliques(g.assocs))]$color <- "Red";
print("Plotting random graph...");
CairoPNG(paste(datafolder, "/", "text-igraph-random.png", sep=""), width=as.numeric(rwidth), height=as.numeric(rheight));
plot(g.assocs, layout=layout.random, vertex.size=4, vertex.label.dist=0);
dev.off();
print("Plotting circle graph...");
CairoPNG(paste(datafolder, "/", "text-igraph-circle.png", sep=""), width=as.numeric(rwidth), height=as.numeric(rheight));
plot(g.assocs, layout=layout.circle, vertex.size=4, vertex.label.dist=0);
dev.off();
print("Plotting sphere graph...");
CairoPNG(paste(datafolder, "/", "text-igraph-sphere.png", sep=""), width=as.numeric(rwidth), height=as.numeric(rheight));
plot(g.assocs, layout=layout.sphere, vertex.size=4, vertex.label.dist=0);
dev.off();
print("Plotting spring graph...");
CairoPNG(paste(datafolder, "/", "text-igraph-spring.png", sep=""), width=as.numeric(rwidth), height=as.numeric(rheight));
plot(g.assocs, layout=layout.spring, vertex.size=4, vertex.label.dist=0);
dev.off();
print("Plotting fruchterman-reingold graph...");
CairoPNG(paste(datafolder, "/", "text-igraph-fruchterman-reingold.png", sep=""), width=as.numeric(rwidth), height=as.numeric(rheight));
plot(g.assocs, layout=layout.fruchterman.reingold, vertex.size=4, vertex.label.dist=0);
dev.off();
print("Plotting kamada-kawai graph...");
CairoPNG(paste(datafolder, "/", "text-igraph-kamada-kawai.png", sep=""), width=as.numeric(rwidth), height=as.numeric(rheight));
plot(g.assocs, layout=layout.kamada.kawai, vertex.size=4, vertex.label.dist=0);
dev.off();
#CairoPNG(paste(datafolder, "/", "text-igraph-reingold-tilford.png", sep=""), width=as.numeric(rwidth), height=as.numeric(rheight));
#plot(g.assocs, layout=layout.reingold.tilford, vertex.size=4, vertex.label.dist=0);
#dev.off();
print("Plotting graphopt graph...");
CairoPNG(paste(datafolder, "/", "text-igraph-graphopt.png", sep=""), width=as.numeric(rwidth), height=as.numeric(rheight));
plot(g.assocs, layout=layout.graphopt, vertex.size=4, vertex.label.dist=0);
dev.off();
print("Done!");
Very interesting. Is there a standard method of deciding when to use which algorithm? Or do you just draw them all and see which one looks best?
Couple of minor things:
1. readline is arguably cleaner than scan for getting user input.
2. [:punct:] includes apostrophes, so a more thourough analysis might require an update to the regex that splits your text.
I love the idea of plotting text with R and igraph. The code you posted is more skeletal. Do you have this code located anywhere in it’s completed entirety? Thanks for sharing!