Package: LSX 1.4.1

LSX: Semi-Supervised Algorithm for Document Scaling

A word embeddings-based semi-supervised model for document scaling Watanabe (2020) <doi:10.1080/19312458.2020.1832976>. LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove). It can generate word vectors on a users-provided corpus or incorporate a pre-trained word vectors.

Authors:Kohei Watanabe [aut, cre, cph]

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NEWS

Peer review:

Bug tracker:https://github.com/koheiw/lsx/issues

On CRAN:

lsaquantedasentiment-analysistext-analysis

18 exports 55 stars 3.65 score 58 dependencies 2 mentions 12 scripts 561 downloads

Last updated 2 months agofrom:1a06b33dd8. Checks:OK: 1 NOTE: 6. Indexed: yes.

Exports:as.coefficients_textmodelas.seedwordsas.statistics_textmodelas.summary.textmodelas.textmodel_lssbootstrap_lsschar_contextcoefficients.textmodel_lsscohesiondiagnosysoptimize_lssseedwordssmooth_lsstextmodel_lsstextplot_componentstextplot_similtextplot_termstextstat_context

Dependencies:clicolorspacedata.tabledigestfansifarverfastmatchfloatggplot2ggrepelgluegtableirlbaisobandISOcodesjsonlitelabelinglatticelgrlifecyclelocfitmagrittrMASSMatrixMatrixExtramgcvmunsellnlmensyllablepillarpkgconfigplyrproxyCquantedaquanteda.textstatsR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2RhpcBLASctlrlangrsparseRSpectrarsvdscalesSnowballCstopwordsstringistringrtibbleutf8vctrsviridisLitewithrxml2yaml