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Leveraging (large) language models for automatic topic labeling. The main function converts a list of top terms into a label for each topic. Hence, it is complementary to any topic modeling package that produces a list of top terms for each topic. While human judgement is indispensable for topic validation (i.e., inspecting top terms and most representative documents), automatic topic labeling can be a valuable tool for researchers in various scenarios.
Version: | 0.2.0 |
Depends: | R (≥ 3.6.0) |
Imports: | checkmate (≥ 1.8.5), httr, progress, stats, jsonlite |
Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
Published: | 2024-10-21 |
DOI: | 10.32614/CRAN.package.topiclabels |
Author: | Jonas Rieger [aut, cre], Fritz Peters [aut], Andreas Fischer [aut], Tim Lauer [aut], André Bittermann [aut] |
Maintainer: | Jonas Rieger <rieger at statistik.tu-dortmund.de> |
BugReports: | https://github.com/PetersFritz/topiclabels/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/PetersFritz/topiclabels |
NeedsCompilation: | no |
Citation: | topiclabels citation info |
Materials: | README |
CRAN checks: | topiclabels results |
Reference manual: | topiclabels.pdf |
Package source: | topiclabels_0.2.0.tar.gz |
Windows binaries: | r-devel: topiclabels_0.2.0.zip, r-release: topiclabels_0.2.0.zip, r-oldrel: topiclabels_0.2.0.zip |
macOS binaries: | r-release (arm64): topiclabels_0.2.0.tgz, r-oldrel (arm64): topiclabels_0.2.0.tgz, r-release (x86_64): topiclabels_0.2.0.tgz, r-oldrel (x86_64): topiclabels_0.2.0.tgz |
Old sources: | topiclabels archive |
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