qdap (version 2.2.9)

chunker: Break Text Into Ordered Word Chunks

Description

Some visualizations and algorithms require text to be broken into chunks of ordered words. chunker breaks text, optionally by grouping variables, into equal chunks. The chunk size can be specified by giving number of words to be in each chunk or the number of chunks.

Usage

chunker(text.var, grouping.var = NULL, n.words, n.chunks, as.string = TRUE,
  rm.unequal = FALSE)

Arguments

text.var

The text variable

grouping.var

The grouping variables. Default NULL generates one word list for all text. Also takes a single grouping variable or a list of 1 or more grouping variables.

n.words

An integer specifying the number of words in each chunk (must specify n.chunks or n.words).

n.chunks

An integer specifying the number of chunks (must specify n.chunks or n.words).

as.string

logical. If TRUE the chunks are returned as a single string. If FALSE the chunks are returned as a vector of single words.

rm.unequal

logical. If TRUE final chunks that are unequal in length to the other chunks are removed.

Value

Returns a list of text chunks.

Examples

# NOT RUN {
with(DATA, chunker(state, n.chunks = 10))
with(DATA, chunker(state, n.words = 10))
with(DATA, chunker(state, n.chunks = 10, as.string=FALSE))
with(DATA, chunker(state, n.chunks = 10, rm.unequal=TRUE))
with(DATA, chunker(state, person, n.chunks = 10))
with(DATA, chunker(state, list(sex, adult), n.words = 10))
with(DATA, chunker(state, person, n.words = 10, rm.unequal=TRUE))

## Bigger data
with(hamlet, chunker(dialogue, person, n.chunks = 10))
with(hamlet, chunker(dialogue, person, n.words = 300))

# }
# NOT RUN {
## with polarity hedonmetrics
dat <- with(pres_debates2012[pres_debates2012$person %in% qcv(OBAMA, ROMNEY), ], 
    chunker(dialogue, list(person, time), n.words = 300))

dat2 <- colsplit2df(list2df(dat, "dialogue", "person&time")[, 2:1])

dat3 <- split(dat2[, -2], dat2$time)
ltruncdf(dat3, 10, 50)

poldat <- lapply(dat3, function(x) with(x, polarity(dialogue, person, constrain = TRUE)))


m <- lapply(poldat, function(x) plot(cumulative(x)))
m <- Map(function(w, x, y, z) {
        w + ggtitle(x) + xlab(y) + ylab(z)
    }, 
        m, 
        paste("Debate", 1:3), 
        list(NULL, NULL, "Duration (300 Word Segment)"), 
        list(NULL, "Cumulative Average Polarity", NULL)
)

library(gridExtra)
do.call(grid.arrange, m)

## By person
## By person
poldat2 <- Map(function(x, x2){

    scores <- with(counts(x), split(polarity, person))
    setNames(lapply(scores, function(y) {
        y <- list(cumulative_average_polarity = y)
        attributes(y)[["constrained"]] <- TRUE
        qdap:::plot.cumulative_polarity(y) + xlab(NULL) + ylab(x2)
    }), names(scores))

}, poldat, paste("Debate", 1:3))

poldat2 <- lapply(poldat2, function(x) {
    x[[2]] <- x[[2]] + ylab(NULL)
    x
})

poldat2[[1]] <- Map(function(x, y) {
        x + ggtitle(y)
    },
        poldat2[[1]], qcv(Obama, Romney)
)

library(gridExtra)
do.call(grid.arrange, unlist(poldat2, recursive=FALSE))
# }