Create Validation Tests for Automated Content Analysis
c(person(given = "Chung-hong", family = "Chan", role = c("aut", "cre"), email = "chainsawtiney@gmail.com", comment = c(ORCID = "0000-0002-6232-7530")), person(given = "Marius", family = "Sältzer", role = c("aut"), email = "msaeltze@mail.uni-mannheim.de", comment = c(ORCID = "0000-0002-8604-4666")))
Intended to create standard human-in-the-loop validity tests for typical automated content analysis such as topic modeling and dictionary-based methods. This package offers a standard workflow with functions to prepare, administer and evaluate a human-in-the-loop validity test. This package provides functions for validating topic models using word intrusion and Topic intrusion tests, as described in Chang et al. (2009) <https://papers.nips.cc/paper/3700-reading-tea-leaves-how-humans-interpret-topic-models>. This package also provides functions for generating gold-standard data which are useful for validating dictionary-based methods. The default settings of all generated tests match those suggested in Chang et al. (2009) and Song et al. (2020) <doi:10.1080/10584609.2020.1723752>.
stm, purrr, tibble, shiny, miniUI, text2vec (>= 0.6), digest,
R6, quanteda, irr, ggplot2, cowplot, dplyr, stats, utils
testthat (>= 2.1.0), BTM, topicmodels, keyATM (>= 0.2.2),
covr, stringr, knitr, rmarkdown

person(given = "Chung-hong",
family = "Chan",
role = c("aut", "cre"),
email = "chainsawtiney@gmail.com",
comment = c(ORCID = "0000-0002-6232-7530"))
testthat (>= 2.1.0), topicmodels, covr, stringr, knitr,
rmarkdown
Chung-hong Chan [aut, cre] (<https://orcid.org/0000-0002-6232-7530>)

Intended to create standard human-in-the-loop validity tests for typical automated content analysis such as topic modeling and dictionary-based methods. This package offers a standard workflow with functions to prepare, administer and evaluate a human-in-the-loop validity test. This package provides functions for validating topic models using word intrusion, topic intrusion (Chang et al. 2009,  <https://papers.nips.cc/paper/3700-reading-tea-leaves-how-humans-interpret-topic-models>) and word set intrusion (Ying et al. Forthcoming) tests. This package also provides functions for generating gold-standard data which are useful for validating dictionary-based methods. The default settings of all generated tests match those suggested in Chang et al. (2009) and Song et al. (2020) <doi:10.1080/10584609.2020.1723752>.
keyATM (>= 0.2.2), purrr, tibble, shiny, miniUI, text2vec (>=
0.6), digest, R6, quanteda (>= 3.0.0), irr, ggplot2, cowplot,
dplyr, cli, stats, utils
testthat (>= 3.0.2), BTM, topicmodels, stm, seededlda, covr,
stringr, knitr, rmarkdown, fs, quanteda.textmodels, shinytest