dfm_analysis: Create a document frequency matrix (sorted in descending...

In till-tietz/rbow: Bag of Words and Document Frequency Analysis for Multiple Dictionaries

Description

Create a document frequency matrix (sorted in descending order) of terms that occur within some window around a given set of words (phenomenon)

Usage

dfm_analysis(
  corpus,
  phenomenon,
  window = 10,
  n_terms = 10,
  filter_dictionary = NULL,
  tf_idf = FALSE,
  filter_ps = FALSE,
  ps = NULL,
  own_regex = FALSE
)

Arguments

corpus	the text or texts to be analyzed as a list of character vectors
phenomenon	a list of character vectors (or list of regular expressions if own_regex == TRUE) with terms around which words will be counted for the dfm
window	number of words left and right of a phenomenon term to be considered for the dfm
n_terms	number of terms displayed in dfm
filter_dictionary	a character vector (or regular expression if own_regex == TRUE) of words to select from the dfm
tf_idf	if TRUE function computes tf-idf metric instead of raw counts
filter_ps	if TRUE enables filtering of results by part of speech (i.e only adjectives and adverbs)
ps	character vector of parts of speech to filter. see selection with unique(tidytext::parts_of_speech[,"pos"])
own_regex	when TRUE allows you to add custom regular expressions for phenomenon and filter_dictionary. when FALSE rbow will construct regular expression from the character vectors you supplied. defaults to FALSE

Value

list of dfms (one dfm per text in corpus)

till-tietz/rbow documentation built on Oct. 21, 2021, 9:16 p.m.