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
Documentation
Team
Luwei Ying
Brandon Stewart
Show author detailsRolesAuthorJacob Montgomery
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 112 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,693 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 06, 2024 with 22 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
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Dependencies
- Imports5 packages
- Suggests2 packages