Calculates multiple readability metrics for texts including Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning FOG index, and others. Optionally includes lexical diversity metrics and sentence statistics.
Usage
calculate_text_readability(
texts,
metrics = c("flesch", "flesch_kincaid", "gunning_fog"),
include_lexical_diversity = TRUE,
include_sentence_stats = TRUE,
doc_names = NULL
)Arguments
- texts
Character vector of texts to analyze
- metrics
Character vector of readability metrics to calculate. Options: "flesch", "flesch_kincaid", "gunning_fog", "smog", "ari", "coleman_liau"
- include_lexical_diversity
Logical, include the MTLD lexical diversity index (default: TRUE)
- include_sentence_stats
Logical, include average sentence length (default: TRUE)
- doc_names
Optional character vector of document names
Examples
# \donttest{
data(SpecialEduTech, package = "TextAnalysisR")
texts <- SpecialEduTech$abstract[1:10]
readability <- calculate_text_readability(texts)
print(readability)
#> Document flesch flesch_kincaid gunning_fog Lexical Diversity (MTLD)
#> 1 Doc 1 19.824902 17.53294 21.21569 107.16222
#> 2 Doc 2 -5.024231 20.41923 24.24615 80.64000
#> 3 Doc 3 5.505682 16.59045 22.35758 40.96000
#> 4 Doc 4 27.617151 14.74849 17.90233 172.57333
#> 5 Doc 5 16.490000 17.17000 20.00000 57.53291
#> 6 Doc 6 14.513863 16.77798 21.36197 65.30157
#> 7 Doc 7 -10.401667 19.18185 24.23704 121.38000
#> 8 Doc 8 26.795461 15.57450 19.74545 64.44045
#> 9 Doc 9 15.338100 16.87522 18.47530 73.67553
#> 10 Doc 10 -2.587500 19.58250 22.93333 123.70400
#> Avg Sentence Length
#> 1 27.66667
#> 2 24.00000
#> 3 16.00000
#> 4 21.50000
#> 5 24.75000
#> 6 21.68750
#> 7 17.00000
#> 8 24.00000
#> 9 22.66667
#> 10 23.50000
# }