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+
+# Script to parse email newsletters from environmental groups
+
+# Note: There doesn't seem to be a good package for ingesting email mbox files in R, 
+# so I have already processed an exported mbox file using python (https://github.com/jarrodparkes/mbox-to-csv)
+
+# PRELIMINARIES, load libraries and data
+
+require(tm)
+require(wordcloud)
+require(stringr)
+
+# Start by generating wordcloud from CCF applications stored in CSV
+
+# Clean data set
+
+newsletters <- Corpus (DirSource("CCF/"))
+ccf <- tm_map(ccf, stripWhitespace)
+ccf <- tm_map(ccf, tolower)
+ccf <- tm_map(ccf, removeNumbers)
+ccf <- tm_map(ccf, removePunctuation)
+
+# tweak by adding extra stopwords, "will"
+
+myStopwords <- c(stopwords('english'), "will", "project")
+
+# tweak by removing extra stopwords, in this example "r"
+# idx <- which(myStopwords == "r")
+# myStopwords <- myStopwords[-idx]
+
+ccf <- tm_map(ccf, removeWords, myStopwords)
+# ccf <- tm_map(ccf, stemDocument)
+ccf <- tm_map(ccf, PlainTextDocument)
+
+# Create word cloud
+
+# wordcloud(ccf, scale=c(5,0.5), max.words=100, random.order=FALSE, rot.per=0.35, use.r.layout=FALSE, colors=brewer.pal(8, "Dark2"))
+# wordcloud(ccf, scale=c(8,.2), min.freq=2, max.words=Inf, random.order=FALSE, rot.per=.15, colors=brewer.pal(8, "Dark2"))
+wordcloud(ccf, scale=c(5,.3), max.words=250, random.order=FALSE, rot.per=0.35, use.r.layout=FALSE, colors=brewer.pal(8, "Dark3"))