DESCRIPTION

Package: LSX
Type: Package
Title: Semi-Supervised Algorithm for Document Scaling
Version: 1.4.2
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) <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.
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,
    irlba,
    rsvd,
    rsparse
RoxygenNote: 7.3.2
Roxygen: list(markdown = TRUE)
BugReports: https://github.com/koheiw/LSX/issues
URL: https://koheiw.github.io/LSX/
Language: en-US