validateIt
Validating Topic Coherence and Topic Labels
By creating crowd-sourcing tasks that can be easily posted and results retrieved using Amazon's Mechanical Turk (MTurk) API, researchers can use this solution to validate the quality of topics obtained from unsupervised or semi-supervised learning methods, and the relevance of topic labels assigned. This helps ensure that the topic modeling results are accurate and useful for research purposes. See Ying and others (2022) doi:10.1101/2023.05.02.538599. For more information, please visit https://github.com/Triads-Developer/Topic_Model_Validation.
- Version1.2.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Ying and others (2022)
- Last release05/16/2023
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Team
Luwei Ying
Brandon Stewart
Show author detailsRolesAuthorJacob Montgomery
Show author detailsRolesAuthor
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- Imports5 packages
- Suggests2 packages