discursive_size {discursive}

Compute the size component of discursive sophistication

Description

This function takes a data frame (data) containing a set of open-ended responses (openends) and additional arguments passed to stm::textProcessor() and stm::prepDocuments() to estimate a structural topic model via stm::stm(). The results of the the structural topic model are used to compute the relative number of topics raised in each open-ended response. The function returns a numeric vector of topic counts re-scaled to range from 0 to 1. See Kraft (2023) for details.

Usage

discursive_size(
  data,
  openends,
  meta,
  args_textProcessor = NULL,
  args_prepDocuments = NULL,
  args_stm = NULL,
  keep_stm = TRUE,
  progress = TRUE
)

Arguments

data

A data frame.

openends

A character vector containing variable names of open-ended responses in data.

meta

A character vector containing topic prevalence covariates included in data. See stm::stm() for details.

args_textProcessor

A named list containing additional arguments passed to stm::textProcessor().

args_prepDocuments

A named list containing additional arguments passed to stm::prepDocuments().

args_stm

A named list containing additional arguments passed to stm::stm().

keep_stm

Logical. If TRUE function returns output of stm::textProcessor(), stm::prepDocuments(), and stm::stm().

progress

Logical. Shows progress bar if TRUE.

Value

A list containing the size component of discursive sophistication as well as the output of stm::textProcessor(), stm::prepDocuments(), and stm::stm().

Examples

discursive_size(data = cces,
                openends = c(paste0("oe0", 1:9), "oe10"),
                meta = c("age", "educ_cont", "pid_cont", "educ_pid", "female"),
                args_prepDocuments = list(lower.thresh = 10),
                args_stm = list(K = 25, seed = 12345))