psychtm: 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). <doi:10.31234/osf.io/62tc3>.
| Version: |
2021.1.0 |
| Depends: |
R (≥ 3.3.0) |
| Imports: |
coda (≥ 0.4), label.switching, methods, Rcpp (≥ 0.11.0), rlang (≥ 0.4.10), tibble (≥ 2.1.3) |
| LinkingTo: |
Rcpp (≥ 0.11.0), RcppArmadillo, RcppProgress (≥ 0.4.2) |
| Suggests: |
spelling, knitr (≥ 1.22), covr, dplyr, ggplot2, lda, testthat (≥ 3.0.2), rmarkdown |
| Published: |
2021-11-02 |
| Author: |
Kenneth Wilcox [aut, cre, cph] |
| Maintainer: |
Kenneth Wilcox <kwilcox3 at nd.edu> |
| BugReports: |
https://github.com/ktw5691/psychtm/issues |
| License: |
LGPL (≥ 3) |
| URL: |
https://github.com/ktw5691/psychtm/ |
| NeedsCompilation: |
yes |
| SystemRequirements: |
C++11 |
| Language: |
en-US |
| Citation: |
psychtm citation info |
| Materials: |
README NEWS |
| CRAN checks: |
psychtm results |
Documentation:
Downloads:
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