Package: LSX 1.5.2

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]

LSX_1.5.2.tar.gz
LSX_1.5.2.zip(r-4.7)LSX_1.5.2.zip(r-4.6)LSX_1.5.2.zip(r-4.5)
LSX_1.5.2.tgz(r-4.6-any)LSX_1.5.2.tgz(r-4.5-any)
LSX_1.5.2.tar.gz(r-4.7-any)LSX_1.5.2.tar.gz(r-4.6-any)
LSX_1.5.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
LSX/json (API)
NEWS

# Install 'LSX' in R:
install.packages('LSX', repos = c('https://koheiw.r-universe.dev', 'https://cloud.r-project.org'))

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

Pkgdown/docs site:https://koheiw.github.io

Datasets:

On CRAN:

Conda:

lsaquantedasentiment-analysistext-analysis

6.41 score 57 stars 25 scripts 808 downloads 2 mentions 19 exports 42 dependencies

Last updated from:dd3dfbed82. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK213
source / vignettesOK169
linux-release-x86_64OK225
macos-release-arm64OK204
macos-oldrel-arm64OK177
windows-develOK235
windows-releaseOK163
windows-oldrelOK178
wasm-releaseOK121

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

Dependencies:clicpp11digestfarverfastmatchggplot2ggrepelgluegtableisobandISOcodesjsonlitelabelinglatticelifecyclelocfitmagrittrMatrixnsyllableplyrproxyCquantedaquanteda.textstatsR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangRSpectraS7scalesSnowballCstopwordsstringistringrvctrsviridisLitewithrxml2yaml

Readme and manuals

Help Manual

Help pageTopics
Convert a list or a dictionary to seed wordsas.seedwords
Create a Latent Semantic Scaling model from various objectsas.textmodel_lss as.textmodel_lss.matrix as.textmodel_lss.numeric as.textmodel_lss.textmodel_lss as.textmodel_lss.textmodel_word2vec
[experimental] Compute polarity scores with different hyper-parametersbootstrap_lss
Extract model coefficients from a fitted textmodel_lss objectcoef.textmodel_lss coefficients.textmodel_lss
Seed words for analysis of left-right political ideologydata_dictionary_ideology
Seed words for analysis of positive-negative sentimentdata_dictionary_sentiment
A fitted LSS model on street protest in Russiadata_textmodel_lss_russianprotests
[experimental] Compute variance ratios with different hyper-parametersoptimize_lss
Prediction method for textmodel_lsspredict.textmodel_lss
Seed words for Latent Semantic Analysisseedwords
Smooth predicted polarity scoressmooth_lss
Fit a Latent Semantic Scaling modeltextmodel_lss textmodel_lss.dfm textmodel_lss.fcm textmodel_lss.tokens
Plot similarity between seed wordstextplot_simil
Plot polarity scores of wordstextplot_terms
Identify context wordschar_context textstat_context