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Is there a better way to create Keyword frequency table in R ?

Answer 1

+1 A:

Here's a slightly refactored version of your manipulations (I don't know much about ggplot2).

bib <- bib[bib$Journal != "",]

resu <- NULL
for(i in 1:nrow(bib)) {
  resu <- rbind(resu,
    data.frame( Journal=as.character(bib$Journal[i]),
                Keyword=strsplit(as.character(bib$Custom3[i]),"/")[[1]],
                Count=1, stringsAsFactors=FALSE ))
}

keywordtable <- aggregate(resu[,"Count",FALSE],
                  by=resu[,c("Journal","Keyword")], sum)

trimkeyword <- subset(keywordtable, Count > 0, drop=TRUE)
trimkeyword <- trimkeyword[order(trimkeyword$Journal,trimkeyword$Keyword),]
trimkeyword$Journal <- factor(trimkeyword$Journal)
trimkeyword$Keyword <- factor(trimkeyword$Keyword)

Joshua Ulrich 2010-10-23 21:04:26

Answer 2

+1 A:

here is a much shorter piece of code to get to keywordtable from the data frame bib

# create list of keywords by journal
res = dlply(bib, .(Journal), summarize, 
            keyw = strsplit(as.character(Custom3), "/"));

# convert into dataframe
res = melt(unlist(res));


res$journal   = rownames(res);
names(res)[1] = 'keyword';
rownames(res) = NULL;

res$journal = with(res, gsub('.keyw', "", journal));
res$journal = with(res, gsub('[[:digit:]]', "", journal));
res$keyword = tolower(res$keyword);

keywordtable = ddply(res, .(journal, keyword), summarize, 
               count = length(keyword));

An alternate visualization would be to create a word cloud of keywords using the snippets package. Here is the code to do that:

library(snippets);
keywords = table(res$keyword);
cloud(keywords, col = col.br(keywords, fit=TRUE))

Ramnath 2010-10-24 01:00:24

Answer 3

A:

Take a look at the text mining package - tm

http://cran.r-project.org/web/packages/tm/index.html

larrydag 2010-10-25 15:20:28

I had found the tmpackage, and while it does have a vignette I didn't spot anything in that or the help that popped out to help my issue. I'll keep looking at it though.

PaulHurleyuk 2010-10-25 21:30:44

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Is there a better way to create Keyword frequency table in R ?

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