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| # | |
| ## 12/21/12 - Ths is my fork of DSparks Denver debate analysis script | |
| # | |
| ########### | |
| # Requirement - run this command to create the "denver.txt" file | |
| # curl https://raw.github.com/dsparks/Test_image/master/Denver_Debate_Transcript.txt > denver.txt | |
| # From: http://www.cnn.com/2012/10/03/politics/debate-transcript/index.html | |
| rm(list = ls()) | |
| doInstall <- TRUE # Change to FALSE if you don't want packages installed. | |
| toInstall <- c("zoo", "tm", "ggplot2", "Snowball") | |
| if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")} | |
| lapply(toInstall, library, character.only = TRUE) | |
| # From: http://www.cnn.com/2012/10/03/politics/debate-transcript/index.html | |
| #Transcript <- readLines("https://raw.github.com/dsparks/Test_image/master/Denver_Debate_Transcript.txt") | |
| con <- file("denver.txt", "r", blocking = FALSE) | |
| Transcript <- readLines(con) | |
| head(Transcript, 20) | |
| Transcript <- data.frame(Words = Transcript, Speaker = NA, stringsAsFactors = FALSE) | |
| Transcript$Speaker[regexpr("LEHRER: ", Transcript$Words) != -1] <- 1 | |
| Transcript$Speaker[regexpr("OBAMA: ", Transcript$Words) != -1] <- 2 | |
| Transcript$Speaker[regexpr("ROMNEY: ", Transcript$Words) != -1] <- 3 | |
| table(Transcript$Speaker) | |
| Transcript$Speaker <- na.locf(Transcript$Speaker) | |
| # Remove moderator: | |
| Transcript <- Transcript[Transcript$Speaker != 1, ] | |
| myCorpus <- Corpus(DataframeSource(Transcript)) | |
| inspect(myCorpus) | |
| myCorpus <- tm_map(myCorpus, tolower) # Make lowercase | |
| myCorpus <- tm_map(myCorpus, removePunctuation, preserve_intra_word_dashes = FALSE) | |
| myCorpus <- tm_map(myCorpus, removeWords, stopwords("english")) # Remove stopwords | |
| myCorpus <- tm_map(myCorpus, removeWords, c("lehrer", "obama", "romney")) | |
| myCorpus <- tm_map(myCorpus, stemDocument) # Stem words | |
| inspect(myCorpus) | |
| docTermMatrix <- DocumentTermMatrix(myCorpus) | |
| docTermMatrix <- inspect(docTermMatrix) | |
| sort(colSums(docTermMatrix)) | |
| table(colSums(docTermMatrix)) | |
| ### so 150 here = items said 7 times | |
| ### so 100 here = items said 10 times | |
| ### so 50 here = items said 17 times | |
| ### so 25 here = items said 24 times | |
| cutoffCount <- tail(sort(colSums(docTermMatrix)), 15)[1] | |
| termCountFrame <- data.frame(Term = colnames(docTermMatrix)) | |
| termCountFrame$Obama <- colSums(docTermMatrix[Transcript$Speaker == 2, ]) | |
| termCountFrame$Romney <- colSums(docTermMatrix[Transcript$Speaker == 3, ]) | |
| termCountFrame$Count <- colSums(docTermMatrix)[termCountFrame$Term] | |
| #termCountFrame$Count <- rowSums(docTermMatrix)[termCountFrame$Term] | |
| head(termCountFrame) | |
| # Plot | |
| ## - this didn't work | |
| ##zp1 <- ggplot(termCountFrame[termCountFrame$Count >= cutoffCount, termCountFrame$Obama >= 1, ]) | |
| zp1 <- ggplot(termCountFrame[termCountFrame$Count >= cutoffCount, ]) | |
| zp1 <- zp1 + geom_text(aes(x = Obama, y = Romney, label = Term)) | |
| print(zp1) |
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This just filters the terms.