Package: LSX Type: Package Title: Semi-Supervised Algorithm for Document Scaling Version: 1.5.2 Authors@R: person("Kohei", "Watanabe", email = "watanabe.kohei@gmail.com", role = c("aut", "cre", "cph")) Description: A word embeddings-based semi-supervised model for document scaling Watanabe (2020) . 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. License: GPL-3 LazyData: TRUE Encoding: UTF-8 Depends: R (>= 3.5.0) Imports: methods, quanteda (>= 2.0), quanteda.textstats, stringi, digest, Matrix, RSpectra, proxyC, stats, ggplot2, ggrepel, reshape2, locfit Suggests: testthat, spelling, knitr, rmarkdown, wordvector (>= 0.5.0), irlba, rsvd, rsparse RoxygenNote: 7.3.3 Roxygen: list(markdown = TRUE) BugReports: https://github.com/koheiw/LSX/issues URL: https://koheiw.github.io/LSX/ Language: en-US Config/pak/sysreqs: libicu-dev libxml2-dev Repository: https://koheiw.r-universe.dev Date/Publication: 2026-07-11 22:53:47 UTC RemoteUrl: https://github.com/koheiw/lsx RemoteRef: HEAD RemoteSha: c66afaa2765fdbd08210a4dd7458a4d969b4849b NeedsCompilation: no Packaged: 2026-07-11 23:09:34 UTC; root Author: Kohei Watanabe [aut, cre, cph] Maintainer: Kohei Watanabe