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Description

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>.

validateIt: An R Package for Topic and Label Validation

Authors: Luwei Ying, Jacob Montgomery and Brandon Stewart

Please email all comments/questions to luwei.ying [AT] wustl.edu

Installation Instructions

The package is currently not available on CRAN. You can install the most recent development version using the devtools package. First you have to install devtools using the following code. Note that you only have to do this once

if(!require(devtools)) install.packages("devtools")

Then you'll need to install the dependency, "pyMTurkR", using the function install_github. If you need to interact with Mturk, be sure to follow the detailed instructions here: github.com/cloudyr/pyMTurkR

devtools::install_github("cloudyr/pyMTurkR")

Now you can install our package

devtools::install_github("Luwei-Ying/validateIt", dependencies=TRUE)

Note that this will install all the packages suggested and required to run our package. It may take a few minutes the first time, but this only needs to be done on the first use. In the future you can update to the most recent development version using the same code.

Metadata

Version

1.2.1

License

Unknown

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