discourse_map: Discourse Mapping

In trinker/qdap: Bridging the Gap Between Qualitative Data and Quantitative Analysis

Description

View the flow of discourse from social actors.

Usage

discourse_map(
  text.var,
  grouping.var,
  edge.constant,
  sep = "_",
  condense = TRUE,
  ...
)

Arguments

text.var	The text variable or a "word_stats" object (i.e., the output of a word_stats function).
grouping.var	The grouping variables. Also takes a single grouping variable or a list of 1 or more grouping variables.
edge.constant	A constant to multiple the edges by. Defaults (if missing) to 2.5 times the number of social actors.
sep	The separator character to use between grouping variables.
condense	logical. If TRUE sentCombine is used to condense text by grouping variable.
...	ignored

Details

For an example of the video generated from the Animate output of discourse_map see: https://www.youtube.com/watch?v=7LcqFZODXNo&feature=youtu.be. An HTML output can be viewed: http://trinker.github.io/qdap_examples/animation_dialogue/.

Value

Returns a list:

raw	The dataframe with to and from columns (the edges) + word counts
edge_word_count	A dataframe of edges and word counts + proportional word count
vertex_word_count	A dataframe of vertices and word counts + proportional word count
plot	An igraph object

Examples

## Not run: 
discourse_map(DATA$state, list(DATA$person, DATA$sex))
x <- with(mraja1, discourse_map(dialogue, person))
x
lview(x)
library(igraph)
plot(visual(x), edge.curved=FALSE)

## Quickly add/remove a title
Title(x) <- "Act 1"
x
Title(x) <- NULL
x

## Augmenting the plot
library(qdapTools)
mygraph <- visual(x)

plot(mygraph, edge.curved=TRUE)

V(mygraph)$sex <- V(mygraph)$name %lc% raj.demographics[, 1:2]
V(mygraph)$color <- ifelse(V(mygraph)$sex=="f", "pink", "lightblue")

plot(mygraph, edge.curved=TRUE)

V(mygraph)$family <- V(mygraph)$name %l+% raj.demographics[, c(1, 3)]
cols <- qcv(blue, red, brown, darkgreen, grey10)
V(mygraph)$label.color <- lookup(V(mygraph)$family, 
    unique(V(mygraph)$family), cols)

plot(mygraph, edge.curved=TRUE)

## Community detection
x <- with(mraja1, discourse_map(dialogue, person))
wc <- walktrap.community(visual(x))
colors <- grDevices::rainbow(max(membership(wc)))
plot(x, vertex.color=colors[membership(wc)])

## Repeated Measures (BASIC EXAMPLE)
##------------------------------

## First merge data and map to discourse per act 
## to separate networks

dat <- key_merge(raj, raj.demographics)
list_dat <- split(dat, dat$act)
plot_dat <- lapply(list_dat, function(x) with(x, discourse_map(dialogue, person)))

opar <- par()$mar
par(mfrow=c(3, 2), mar=c(0, 0, 3, 0))

lapply(seq_along(plot_dat), function(i){
    plot(plot_dat[[i]])
    graphics::mtext(paste("Act", names(plot_dat)[i]), side=3)
})


## Repeated Measures (EXTENDED EXAMPLE)
##------------------------------
fam_key <- data.frame(fam=unique(raj.demographics$fam.aff),
    cols=qcv(blue, grey10, red, orange), 
    stringsAsFactors = FALSE)

par(mfrow=c(3, 2), mar=c(0, 1, 3, 1))
lapply(seq_along(plot_dat), function(i){

    THE_PLOT <- visual(plot_dat[[i]])

    V(THE_PLOT)$sex <- V(THE_PLOT)$name %l% raj.demographics[, 1:2]
    V(THE_PLOT)$color <- ifelse(V(THE_PLOT)$sex=="f", "pink", "lightblue")
    V(THE_PLOT)$family <- V(THE_PLOT)$name %lc+% raj.demographics[, c(1, 3)]
    V(THE_PLOT)$label.color <- lookup(V(THE_PLOT)$family, fam_key)

    plot(THE_PLOT, edge.curved=TRUE)
    graphics::mtext(paste("Act", names(plot_dat)[i]), side=3)
})
frame()
bords <- rep("black", 7)
bords[3] <- "white"
legend(.29, .95, c("Female", "Male", NA, as.character(fam_key[, 1])), 
    fill=c("pink", "lightblue", NA, fam_key[, 2]), border=bords, cex=1.5) 

## Reset graphics margins
par(mar=opar)

## ANIMATION
#===========
test <- discourse_map(DATA$state, list(DATA$person))

## Very quick, hard to see
Animate(test)

pdf("test.pdf")
    par(mar=c(0, 0, 1, 0))
    Animate(test, title="Test Plot")
dev.off()

## Animate it
##-----------
library(animation)
library(igraph)

loc <- folder(animation_dialogue)
ans <- Animate(test)

## Set up the plotting function
oopt <- animation::ani.options(interval = 0.1)

FUN <- function() {
    lapply(seq_along(ans), function(i) {
        par(mar=c(0, 0, 1, 0))
        set.seed(10)
        plot.igraph(ans[[i]], edge.curved=TRUE, layout=layout.circle)
        graphics::mtext("Discourse Map", side=3)
        animation::ani.pause()
    })
}

## Detect OS
type <- if(.Platform$OS.type == "windows") shell else system
saveGIF(FUN(), interval = 0.1, outdir = loc, cmd.fun = type)

saveVideo(FUN(), video.name = "discourse_map.avi", interval = 0.1, outdir = loc)

saveLatex(FUN(), autoplay = TRUE, loop = FALSE, latex.filename = "tester.tex", 
    caption = "animated dialogue", outdir = loc, ani.type = "pdf", 
    ani.dev = "pdf", ani.width = 5, ani.height = 5.5, interval = 0.1)

saveHTML(FUN(), autoplay = FALSE, loop = TRUE, verbose = FALSE, 
    outdir = file.path(loc, "new"), single.opts = 
    "'controls': ['first', 'previous', 'play', 'next', 'last', 'loop', 'speed'], 'delayMin': 0")
    
    
## More Elaborate Layout
test2 <- with(mraja1, discourse_map(dialogue, person))

loc2 <- folder(animation_dialogue2)
ans2 <- Animate(test2)
## Set up the plotting function
oopt <- animation::ani.options(interval = 0.1)

FUN3 <- function() {
    lapply(seq_along(ans2), function(i) {
        par(mar=c(0, 0, 1, 0))
        set.seed(10)
        plot.igraph(ans2[[i]], edge.curved=TRUE, layout=layout.auto)
        graphics::mtext("Discourse Map\nRomeo and Juliet: Act 1", side=3)
        animation::ani.pause()
    })
}

saveHTML(FUN3(), autoplay = FALSE, loop = FALSE, verbose = FALSE,
    outdir = file.path(loc2, "new"), single.opts =
    "'controls': ['first', 'play', 'loop', 'speed'], 'delayMin': 0")
    
saveVideo(FUN3(), video.name = "discourse_map.avi", interval = 0.2, 
    outdir = loc2)    

## End(Not run)

trinker/qdap documentation built on Sept. 30, 2020, 6:28 p.m.