A word cloud (or tag cloud) can be an handy tool when you need to highlight the most commonly cited words in a text using a quick visualization. Of course, you can use one of the several on-line services, such as wordle or tagxedo , very feature rich and with a nice GUI. Being an R enthusiast, I always wanted to produce this kind of images within R and now, thanks to the recently released Ian Fellows’ wordcloud package, finally I can!
In order to test the package I retrieved the titles of the XKCD web comics included in my RXKCD package and produced a word cloud based on the titles’ word frequencies calculated using the powerful tm package for text mining (I know, it is like killing a fly with a bazooka!).

library(RXKCD)
library(tm)
library(wordcloud)
library(RColorBrewer)
path <- system.file("xkcd", package = "RXKCD")
datafiles <- list.files(path)
xkcd.df <- read.csv(file.path(path, datafiles))
xkcd.corpus <- Corpus(DataframeSource(data.frame(xkcd.df[, 3])))
xkcd.corpus <- tm_map(xkcd.corpus, removePunctuation)
xkcd.corpus <- tm_map(xkcd.corpus, tolower)
xkcd.corpus <- tm_map(xkcd.corpus, function(x) removeWords(x, stopwords("english")))
tdm <- TermDocumentMatrix(xkcd.corpus)
m <- as.matrix(tdm)
v <- sort(rowSums(m),decreasing=TRUE)
d <- data.frame(word = names(v),freq=v)
pal <- brewer.pal(9, "BuGn")
pal <- pal[-(1:2)]
png("wordcloud.png", width=1280,height=800)
wordcloud(d$word,d$freq, scale=c(8,.3),min.freq=2,max.words=100, random.order=T, rot.per=.15, colors=pal, vfont=c("sans serif","plain"))
dev.off()

As a second example,  inspired by this post from the eKonometrics blog, I created a word cloud from the description of  3177 available R packages listed at http://cran.r-project.org/web/packages.

require(XML)
require(tm)
require(wordcloud)
require(RColorBrewer)
u = "http://cran.r-project.org/web/packages/available_packages_by_date.html"
t = readHTMLTable(u)[[1]]
ap.corpus <- Corpus(DataframeSource(data.frame(as.character(t[,3]))))
ap.corpus <- tm_map(ap.corpus, removePunctuation)
ap.corpus <- tm_map(ap.corpus, tolower)
ap.corpus <- tm_map(ap.corpus, function(x) removeWords(x, stopwords("english")))
ap.tdm <- TermDocumentMatrix(ap.corpus)
ap.m <- as.matrix(ap.tdm)
ap.v <- sort(rowSums(ap.m),decreasing=TRUE)
ap.d <- data.frame(word = names(ap.v),freq=ap.v)
table(ap.d$freq)
pal2 <- brewer.pal(8,"Dark2")
png("wordcloud_packages.png", width=1280,height=800)
wordcloud(ap.d$word,ap.d$freq, scale=c(8,.2),min.freq=3,
max.words=Inf, random.order=FALSE, rot.per=.15, colors=pal2)
dev.off()

As a third example, thanks to Jim's comment, I take advantage of Duncan Temple Lang's RNYTimes package to access user-generate content on the NY Times and produce a wordcloud of 'today' comments on articles.
Caveat: in order to use the RNYTimes package you need a API key from The New York Times which you can get by registering to the The New York Times Developer Network (free of charge) from here.

require(XML)
require(tm)
require(wordcloud)
require(RColorBrewer)
install.packages(packageName, repos = "http://www.omegahat.org/R", type = "source")
require(RNYTimes)
my.key <- "your API key here"
what= paste("by-date", format(Sys.time(), "%Y-%m-%d"),sep="/")
# what="recent"
recent.news <- community(what=what, key=my.key)
pagetree <- htmlTreeParse(recent.news, error=function(...){}, useInternalNodes = TRUE)
x <- xpathSApply(pagetree, "//*/body", xmlValue)
# do some clean up with regular expressions
x <- unlist(strsplit(x, "\n"))
x <- gsub("\t","",x)
x <- sub("^[[:space:]]*(.*?)[[:space:]]*$", "\\1", x, perl=TRUE)
x <- x[!(x %in% c("", "|"))]
ap.corpus <- Corpus(DataframeSource(data.frame(as.character(x))))
ap.corpus <- tm_map(ap.corpus, removePunctuation)
ap.corpus <- tm_map(ap.corpus, tolower)
ap.corpus <- tm_map(ap.corpus, function(x) removeWords(x, stopwords("english")))
ap.tdm <- TermDocumentMatrix(ap.corpus)
ap.m <- as.matrix(ap.tdm)
ap.v <- sort(rowSums(ap.m),decreasing=TRUE)
ap.d <- data.frame(word = names(ap.v),freq=ap.v)
table(ap.d$freq)
pal2 <- brewer.pal(8,"Dark2")
png("wordcloud_NewYorkTimes_Community.png", width=1280,height=800)
wordcloud(ap.d$word,ap.d$freq, scale=c(8,.2),min.freq=2,
max.words=Inf, random.order=FALSE, rot.per=.15, colors=pal2)
dev.off()