automated_readability_index

From qdap v0.2.0 by Tyler Rinker

Readability Measures

automated_readability_index - Apply Automated Readability Index to transcript(s) by zero or more grouping variable(s). coleman_liau - Apply Coleman Liau Index to transcript(s) by zero or more grouping variable(s). SMOG - Apply SMOG Readability to transcript(s) by zero or more grouping variable(s). flesch_kincaid - Flesch-Kincaid Readability to transcript(s) by zero or more grouping variable(s). fry - Apply Fry Readability to transcript(s) by zero or more grouping variable(s). linsear_write - Apply Linsear Write Readability to transcript(s) by zero or more grouping variable(s).

Keywords: , index, write, readability, Automated, Coleman, Flesch-Kincaid, Fry, Liau, Linsear, SMOG

Usage

automated_readability_index(text.var,
    grouping.var = NULL, rm.incomplete = FALSE, ...)

  coleman_liau(text.var, grouping.var = NULL,
    rm.incomplete = FALSE, ...)

  SMOG(text.var, grouping.var = NULL, output = "valid",
    rm.incomplete = FALSE, ...)

  flesch_kincaid(text.var, grouping.var = NULL,
    rm.incomplete = FALSE, ...)

  fry(text.var, grouping.var = NULL, labels = "automatic",
    rm.incomplete = FALSE, ...)

  linsear_write(text.var, grouping.var = NULL,
    rm.incomplete = FALSE, ...)

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.
rm.incomplete: logical. If TRUE removes incomplete sentences from the analysis.
...: Other arguments passed to end_inc.
output: A character vector character string indicating output type. One of "valid" (default and congruent with McLaughlin's intent) or "all".
labels: A character vector character string indicating output type. One of "automatic" (default; adds labels automatically) or "click" (interactive).

Value

Returns a dataframe with selected readability statistic by grouping variable(s). The frey function returns a graphic representation of the readability as well as a list of two dataframe: 1) SENTENCES_USED and 2) SENTENCE_AVERAGES.

Warning

Many of the indices (e.g. Automated Readability Index) are derived from word difficulty (letters per word) and sentence difficulty (words per sentence). If you have not run the sentSplit function on your data the results may not be accurate.

References

Coleman, M., & Liau, T. L. (1975). A computer readability formula designed for machine scoring. Journal of Applied Psychology, Vol. 60, pp. 283-284. Flesch R. (1948). A new readability yardstick. Journal of Applied Psychology. Vol. 32(3), pp. 221-233. doi: 10.1037/h0057532. Gunning, T. G. (2003). Building Literacy in the Content Areas. Boston: Allyn & Bacon. McLaughlin, G. H. (1969). SMOG Grading: A New Readability Formula. Journal of Reading, Vol. 12(8), pp. 639-646. Senter, R. J., & Smith, E. A.. (1967) Automated readability index. Technical Report AMRLTR-66-220, University of Cincinnati, Cincinnati, Ohio.

Examples

AR1 <- with(rajSPLIT, automated_readability_index(dialogue, list(person, act)))
htruncdf(AR1,, 15)
AR2 <- with(rajSPLIT, automated_readability_index(dialogue, list(sex, fam.aff)))
htruncdf(AR2,, 15)

CL1 <- with(rajSPLIT, coleman_liau(dialogue, list(person, act)))
head(CL1)
CL2 <- with(rajSPLIT, coleman_liau(dialogue, list(sex, fam.aff)))
head(CL2)

SM1 <- with(rajSPLIT, SMOG(dialogue, list(person, act)))
head(SM1)
SM2 <- with(rajSPLIT, SMOG(dialogue, list(sex, fam.aff)))
head(SM2)

FL1 <- with(rajSPLIT, flesch_kincaid(dialogue, list(person, act)))
head(FL1)
FL2 <-  with(rajSPLIT, flesch_kincaid(dialogue, list(sex, fam.aff)))
head(FL2)

FR <- with(rajSPLIT, fry(dialogue, list(sex, fam.aff)))
htruncdf(FR$SENTENCES_USED)
head(FR$SENTENCE_AVERAGES)

LW1 <- with(rajSPLIT, linsear_write(dialogue, list(person, act)))
head(LW1)
LW2 <- with(rajSPLIT, linsear_write(dialogue, list(sex, fam.aff)))
head(LW2)

Documentation reproduced from package qdap, version 0.2.0, License: GPL-2

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