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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 |
| 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 |
Documentation:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.