dispersion_plot(text.var, match.terms, grouping.var = NULL, rm.vars = NULL, color = "blue", bg.color = "grey90", horiz.color = "grey85", total.color = "black", symbol = "|", title = "Lexical Dispersion Plot", rev.factor = TRUE, wrap = "'", xlab = "Dialogue (Words)", ylab = NULL, size = 4, plot = TRUE, char2space = "~~", apostrophe.remove = FALSE, scales = "free", space = "free", ...)
NULL
generates
one word list for all text. Also takes a single grouping variable or a list
of 1 or more grouping variables.NULL
generates
one facet for all text. Also takes a single repeated measures variable or
a list of 1 or more grouping variables.horiz.color = bg.color
to eliminate.NULL
totals are dropped."|"
.TRUE
reverses the plot order of the
factors."'"
, use ""
to remove.TRUE
the plot will automatically plot.
The user may wish to set to FALSE
for use in knitr, sweave, etc.
to add additional plot layers.TRUE
removes apostrophes from
the output."fixed"
, the default), free
("free"
), or free in one dimension ("free_x"
, "free_y"
)"fixed"
, the default, all panels have the same size.
If "free_y"
their height will be proportional to the length of the y
scale; if "free_x"
their width will be proportional to the length of
the x scale; or if "free"
both height and width will vary.strip
.Plots a dispersion plot and invisibly returns the ggplot2 object.
Generate a lexical dispersion plot of terms.
The match.terms is character sensitive. Spacing is an important way to grab specific words and requires careful thought. Using "read" will find the words "bread", "read" "reading", and "ready". If you want to search for just the word "read" you'd supply a vector of c(" read ", " reads", " reading", " reader").
## <strong>Not run</strong>: # term_match(raj$dialogue, c(" love ", "love", " night ", "night")) # dispersion_plot(raj$dialogue, c(" love ", "love", " night ", "night")) # dispersion_plot(raj$dialogue, c("love", "night"), rm.vars = raj$act) # with(rajSPLIT , dispersion_plot(dialogue, c("love", "night"), # grouping.var = list(fam.aff, sex), rm.vars = act)) # # ## With grouping variables # with(rajSPLIT , dispersion_plot(dialogue, c("love", "night"), # grouping.var = sex, rm.vars = act)) # # ## Drop total with `total.color = NULL` # with(rajSPLIT , dispersion_plot(dialogue, c("love", "night"), # grouping.var = sex, rm.vars = act, total.color = NULL)) # # ## Change color scheme # with(rajSPLIT, dispersion_plot(dialogue, c("love", "night"), # bg.color = "black", grouping.var = list(fam.aff, sex), # color = "yellow", total.color = "white", horiz.color="grey20")) # # ## Use `word_list` # ## Presidential debates by all # wrds <- word_list(pres_debates2012$dialogue, stopwords = Top200Words) # wrds2 <- spaste(wrds[["rfswl"]][["all"]][, "WORD"]) # wrds2 <- c(" governor~~romney ", wrds2[-c(3, 12)]) # with(pres_debates2012 , dispersion_plot(dialogue, wrds2, rm.vars = time)) # # ## Presidential debates by person # dat <- pres_debates2012 # dat <- dat[dat$person %in% qcv(ROMNEY, OBAMA), ] # # wordlist <- c(" tax", " health", " rich ", "america", " truth", # " money", "cost", " governnor", " president", " we ", # " job", " i ", " you ", " because ", " our ", " years ") # # with(dat, dispersion_plot(dialogue, wordlist, total.color = NULL, # bg.color = "white", grouping.var = person, rm.vars = time, # color = "black", horiz.color="grey80")) # # wordlist2 <- c(" i'd ", " i'll ", " i'm ", " i've ", " i ", # " we'd ", " we'll ", " we're ", " we've ", " we ", # " you'd ", " you'll ", " you're ", " you've ", " you ", " your ", # " he'd ", " he'll ", " he's ", " he ") # # with(dat, dispersion_plot(dialogue, wordlist2, # bg.color = "black", grouping.var = person, rm.vars = time, # color = "yellow", total.color = NULL, horiz.color="grey20")) # # with(dat, dispersion_plot(dialogue, wordlist2, # bg.color = "black", grouping.var = person, rm.vars = time, # color = "red", total.color = "white", horiz.color="grey20")) # # ## `match.terms` as a named list # wordlist3 <- list( # I = c(" i'd ", " i'll ", " i'm ", " i've ", " i "), # we = c(" we'd ", " we'll ", " we're ", " we've ", " we "), # you = c(" you'd ", " you'll ", " you're ", " you've ", " you ", " your "), # he = c(" he'd ", " he'll ", " he's ", " he ") # ) # # with(dat, dispersion_plot(dialogue, wordlist3, # bg.color = "grey60", grouping.var = person, rm.vars = time, # color = "blue", total.color = "grey40", horiz.color="grey20")) # # colsplit2df(scores(with(dat, termco(dialogue, list(time, person), wordlist3)))) # # ## Extras: # ## Reverse facets # # x <- with(pres_debates2012 , dispersion_plot(dialogue, wrds2, rm.vars = time)) # # ## function to reverse ggplot2 facets # rev_facet <- function(x) { # names(x$facet)[1:2] <- names(x$facet)[2:1] # print(x) # } # # rev_facet(x) # ## <strong>End(Not run)</strong>
term_match