topiclabels: Automated Topic Labeling with Language Models

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: 0.1.0
Depends: R (≥ 3.6.0)
Imports: checkmate (≥ 1.8.5), httr, progress, stats, jsonlite
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-07-27
DOI: 10.32614/CRAN.package.topiclabels
Author: Jonas Rieger ORCID iD [aut, cre], Fritz Peters ORCID iD [aut], Andreas Fischer ORCID iD [aut], Tim Lauer ORCID iD [aut], André Bittermann ORCID iD [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

Documentation:

Reference manual: topiclabels.pdf

Downloads:

Package source: topiclabels_0.1.0.tar.gz
Windows binaries: r-devel: topiclabels_0.1.0.zip, r-release: topiclabels_0.1.0.zip, r-oldrel: topiclabels_0.1.0.zip
macOS binaries: r-release (arm64): topiclabels_0.1.0.tgz, r-oldrel (arm64): topiclabels_0.1.0.tgz, r-release (x86_64): topiclabels_0.1.0.tgz, r-oldrel (x86_64): topiclabels_0.1.0.tgz

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