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LSX

1.5.2

Semi-Supervised Algorithm for Document Scaling

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7.8Kdownloads / year
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Overview

About
Maintained by Kohei WatanabeFirst published 2020-09-0927 releasesCRAN page ↗GitHub ↗

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.

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CRAN checks
13OK
Slowest check: 7.0 min · r-devel-linux-x86_64-fedora-clang
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  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

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Repository

Repository
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4Contributors
text-analysislsaquantedasentiment-analysis
1,010 commits · Last activity 2026-07-11 · 0% stars, 30d

Repository practices

Upstream repositoryBeta

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Dependencies

Declared dependencies
18 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5.0
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Code & Tests

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Package Timeline

27 releases. R releases are shown for context.

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Package metadata

First published
2020-09-09
Total releases
27 / 6 yrs
License
GPL-3 OSI
Download size
1.6 MB
Installed size
not tracked yet
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