question_type: Count of Question Type

In trinker/qdap2: Bridging the gap between qualitative data and quantitative analysis

Description

Transcript apply question counts.

Usage

  question_type(text.var, grouping.var = NULL,
    neg.cont = FALSE, percent = TRUE, zero.replace = 0,
    digits = 2)

Arguments

text.var	The text variable
grouping.var	The grouping variables. Default NULL generates one output for all text. Also takes a single grouping variable or a list of 1 or more grouping variables.
neg.cont	logical. IF TRUE provides separate counts for the negative contraction forms of the interrogative words.
percent	logical. If TRUE output given as percent. If FALSE the output is proportion.
zero.replace	Value to replace 0 values with.
digits	Integer; number of decimal places to round when printing.

Details

The algorithm searches for the following interrogative words (and optionally, their negative contraction form as well):

1) whose 2) whom 3) who 4) where 5) what 6) which 7) why 8) when 9) were 10) was 11) does 12) did 13) do 14) is 15) are 16) will 17) how 18) should 19) could 20) would 21) shall 22) may 23) might 24) must 25) can 26) has 27) have 28) had 29) ok 30) right 31) correct 32) implied do/does

The interrogative word that is found first (with the exception of "ok", "right" and "correct") in the question determines the sentence type. "ok", "right" and "correct" sentence types are determined if the sentence is a question with no other interrogative words found and "ok", "right" or "correct" is the last word of the sentence. Those interrogative sentences beginning with the word "you" are categorized as implying do or does question type, though the use of do/does is not explicit. Those with undetermined sentence type are labeled unknown.

Value

Returns a list of:

raw	A dataframe of the questions used in the transcript and their type.
count	A dataframe of total questions (tot.quest) and counts of question types (initial interrogative word) by grouping variable(s).
rnp	Dataframe of the frequency and proportions of question types by grouping variable.
missing	The row numbers of the missing data (excluded from analysis).
percent	The value of percent used for plotting purposes.
zero.replace	The value of zero.replace used for plotting purposes.

Examples

(x <- question_type(DATA$state, DATA$person))
truncdf(x$raw, 15)
x$count
plot(x)
plot(x, label = TRUE)
plot(x, label = TRUE, text.color = "red")
question_type(DATA$state, DATA$person, percent = FALSE)
DATA[8, 4] <- "Won't I distrust you?"
question_type(DATA$state, DATA$person)
DATA <- qdap::DATA
with(DATA, question_type(state, list(sex, adult)))

out1 <- with(mraja1spl, question_type(dialogue, person))
## out1
out2 <- with(mraja1spl, question_type(dialogue, list(sex, fam.aff)))
## out2
out3 <- with(mraja1spl, question_type(dialogue, list(sex, fam.aff),
   percent = FALSE))
plot(out3, label = TRUE, lab.digits = 3)

trinker/qdap2 documentation built on May 31, 2019, 9:47 p.m.