recordtest

Local record generated by the <code>recordTasks</code> function.

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>.

Luwei Ying

validateIt

Validating Topic Coherence and Topic Labels

Jacob Montgomery

Brandon Stewart

recordtest function

A list of two data frames.<dl>
<dt><code>data.frame1</code></dt>
<dd>A data frame of tasks with the <code>optcrt</code> indicating the 
machine preficted choice.</dd><dt><code>data.frame2</code></dt>
<dd>A data frame of tasks with randomized choices. 
Exactly the same with what would be sent online.</dd>
</dl>

Format

Example Local Record of the R4WSI Tasks — recordtest

A list of two data frames.<dl>
<dt><code>data.frame1</code></dt>
<dd>A data frame of tasks with the <code>optcrt</code> indicating the 
machine preficted choice.</dd>

<dt><code>data.frame2</code></dt>
<dd>A data frame of tasks with randomized choices. 
Exactly the same with what would be sent online.</dd>


</dl>

recordtest: Example Local Record of the R4WSI Tasks

Description

Usage

Arguments

Format

Details