Create Validation Tests for Automated Content Analysis R package oolong version 0.7.0 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. 2021) <doi:10.1017/pan.2021.33> 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>. Software Depends: R (>= 3.5.0) Imports: seededlda, purrr, tibble, shiny, digest, R6, quanteda (>= 3.0.0), icr, ggplot2, cowplot, cli, stats, utils Suggests: keyATM (>= 0.2.2), testthat (>= 3.0.2), text2vec (>= 0.6), BTM, dplyr, topicmodels, stm, covr, knitr, rmarkdown, fs, quanteda.textmodels, shinytest2 Chung-hong Chan <chainsawtiney@gmail.com> Comprehensive R Archive Network (CRAN) Chung-hong Chan [aut, cre] (ORCID: <https://orcid.org/0000-0002-6232-7530>), Marius Sältzer [aut] (ORCID: <https://orcid.org/0000-0002-8604-4666>) LGPL (>= 2.1) 2026-05-07 application/tgz https://CRAN.R-project.org/package=oolong doi:10.32614/CRAN.package.oolong