Package: keyATM 0.5.2

Shusei Eshima

keyATM: Keyword Assisted Topic Models

Fits keyword assisted topic models (keyATM) using collapsed Gibbs samplers. The keyATM combines the latent dirichlet allocation (LDA) models with a small number of keywords selected by researchers in order to improve the interpretability and topic classification of the LDA. The keyATM can also incorporate covariates and directly model time trends. The keyATM is proposed in Eshima, Imai, and Sasaki (2024) <doi:10.1111/ajps.12779>.

Authors:Shusei Eshima [aut, cre], Tomoya Sasaki [aut], Kosuke Imai [aut], Chung-hong Chan [ctb], Romain François [ctb], William Lowe [ctb], Seo-young Silvia Kim [ctb]

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keyATM.pdf |keyATM.html✨
keyATM/json (API)
NEWS

Peer review:

Bug tracker:https://github.com/keyatm/keyatm/issues

On CRAN:

latent-dirichlet-allocationnatural-language-processingpolitical-sciencercpprcppeigensocial-sciencetopic-models

22 exports 98 stars 4.21 score 59 dependencies 61 scripts 604 downloads

Last updated 5 months agofrom:022d7e40f2. Checks:OK: 7 NOTE: 2. Indexed: yes.

Exports:by_strata_DocTopicby_strata_TopicWordcovariates_getcovariates_infokeyATMkeyATM_readkeyATMvbmultiPGregplot_alphaplot_modelfitplot_piplot_timetrendplot_topicpropread_keywordssave_figsemantic_coherencetop_docstop_topicstop_wordsvalues_figvisualize_keywordsweightedLDA

Dependencies:clicodetoolscolorspacecpp11digestdplyrfansifarverfastmapfastmatchfsfuturefuture.applygenericsggplot2ggrepelglobalsgluegtableisobandISOcodesjsonlitelabelinglatticelifecyclelistenvmagrittrMASSMatrixmatrixNormalmgcvmunsellmvtnormnlmeparallellypgdrawpillarpkgconfigpurrrquantedaR6RColorBrewerRcppRcppEigenrlangscalesSnowballCstopwordsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrxml2yaml