Text Mining Methods for Psychological Research

Provides text mining methods for social science research. The package implements estimation, inference, summarization, and goodness-of-fit methods for topic models including Latent Dirichlet Allocation (LDA), supervised LDA, and supervised LDA with covariates using Bayesian Markov Chain Monte Carlo. A description of the key models and estimation methods is available in Wilcox, Jacobucci, Zhang, & Ammerman (2021). .


Reference manual

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2021.1.0 by Kenneth Wilcox, 25 days ago


Report a bug at https://github.com/ktw5691/psychtm/issues

Browse source code at https://github.com/cran/psychtm

Authors: Kenneth Wilcox [aut, cre, cph]

Documentation:   PDF Manual  

LGPL (>= 3) license

Imports coda, label.switching, methods, Rcpp, rlang, tibble

Suggests spelling, knitr, covr, dplyr, ggplot2, lda, testthat, rmarkdown

Linking to Rcpp, RcppArmadillo, RcppProgress

System requirements: C++11

See at CRAN