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