Package 'highlightr'

Mapping Collocation Frequency to Source Document

Description

This function provides the frequency of collocations in comments that correspond to the provided source document.

Usage

collocation_frequency(
  tbl,
  source_row,
  text_column,
  collocate_length = 5,
  fuzzy = FALSE,
  n_bands = 50,
  threshold = 0.7,
  n_gram_width = 4,
  band_width = 8
)

Arguments

tbl	data frame containing documents, where each row represents a document
source_row	row containing text to be treated as source
text_column	string indicating the name of the column containing derivative text
collocate_length	the length of the collocation. Default is 5
fuzzy	whether or not to use fuzzy matching in collocation calculations
n_bands	number of bands used in MinHash algorithm passed to zoomerjoin::jaccard_right_join(). Default is 50
threshold	Jaccard distance threshold to be considered a match passed to zoomerjoin::jaccard_right_join(). Default is 0.7
n_gram_width	width of n-grams used in Jaccard distance calculation passed to zoomerjoin::jaccard_right_join(). Default is 4
band_width	width of band used in MinHash algorithm passed to zoomerjoin::jaccard_right_join(). Default is 8

Details

Collocations are sequences of words present in the source document. For example, the phrase "the blue bird flies" contains one collocation of length 4 ("the blue bird flies"), two collocations of length 3 ("the blue bird" and "blue bird flies"), and three collocations of length 2 ("the blue", "blue bird", and "bird flies"). This function counts the number of corresponding phrases in the 'notes', or the derivative documents. This count is divided by the number of times the phrase occurs in the source document. When fuzzy matching is included, indirect matches are included with a weight of (n*d)/m, where n is the frequency of the fuzzy collocation, d is the Jaccard similarity between the transcript and note collocation, and m is the number of closest matches for the note collocation.

Value

a dataframe of the transcript document with collocation values by word

Examples

src_row <- which(notepad_example$ID=="source")
merged_frequency <- collocation_frequency(notepad_example, src_row, "Text")

---

Map collocation to ggplot object

Description

This assigns colors based on frequency to the words in the transcript.

Usage

collocation_plot(
  frequency_doc,
  colors = c("#f251fc", "#f8ff1b"),
  values = "Freq",
  order = "word_num",
  text = "words"
)

Arguments

frequency_doc	document of frequencies (returned from collocation_frequency())
colors	list for color specification for the gradient. Default is c("#f251fc","#f8ff1b")
values	column name of values to use in gradient calculation. Default is "Freq", corresponding to document returned from collocation_frequency()
order	column name corresponding to the the word order of the text. Default is "word_num", corresponding to the document returned from collocation_frequency()
text	column name corresponding to text to map the gradient to. Default is "words", corresponding to the document returned from collocation_frequency()

Value

list of plot, plot object, and frequency

Examples

# Identify Source Row
src_row <- which(notepad_example$ID=="source")
merged_frequency <- collocation_frequency(notepad_example, src_row, "Text")
# Create a plot object to assign colors based on frequency
freq_plot <- collocation_plot(merged_frequency)

---

Create Highlighted Testimony

Description

Adds html tags to create a highlighted testimony corresponding to word frequency. To render correctly, the object produced from highlighted_text() can be added outside of a code chunk in an .Rmd document in the `r highlighted_text()` format. Alternatively, the html output can be saved by using the xml2 package as follows: xml2::write_html(xml2::read_html(highlighted_text(), "filepath.html"))

Usage

highlighted_text(plot_object, labels = c("", ""))

Arguments

plot_object	plot object resulting from collocation_plot()
labels	lower and upper labels for the gradient scale

Value

html code for highlighted text

Examples

# Identify Source Row
src_row <- which(notepad_example$ID=="source")
# Calculate Frequency
merged_frequency <- collocation_frequency(notepad_example, src_row, "Text")
# Create a plot object to assign colors based on frequency
freq_plot <- collocation_plot(merged_frequency)
# Add html tags to create a highlighted version of the source document
page_highlight <- highlighted_text(freq_plot, merged_frequency)

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Comment Example Dataset

Description

Participant comments for the initial description used in the jury perception study

Usage

notepad_example

Format

notepad_example

A data frame with 126 rows and 2 columns:

ID

Participant Identifier, as well as source document identifier

Text

Participant notes, as well as source transcript

Source

Jury Perception Study (see Rogers (2024) https://digitalcommons.unl.edu/dissertations/AAI31240449/)

---

Wikipedia Edit History for "Highlighter"

Description

Text corresponding to versions of the Wikipedia article for Highlighter

Usage

wiki_pages

Format

wiki_pages

A data frame with 300 rows and 1 column:

page_notes

text of the Wikipedia page for Highlighter

Source

Wikipedia: https://en.wikipedia.org/w/index.php?title=Highlighter&action=history

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