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[D] Implementation of CorEx in R?

I recently got turned on to the idea of Topic modeling by way of Correlation Explanation (CorEx) vis-a-vis this post:

https://medium.com/pew-research-center-decoded/overcoming-the-limitations-of-topic-models-with-a-semi-supervised-approach-b947374e0455

I found an implementation in Python here:

https://github.com/gregversteeg/corex_topic

For those familiar with LDA (Latent Dirichlet Allocation), oftentimes the resulting topics don’t make very much sense. Often the beta probabilities (word-to-topic) are so similar that any classification is arbitrary at best, and more often, simply meaningless.

CorEx provides the ability to “anchor” topics to specific terms, providing a semi-supervised approach to topic modeling. Sounds exciting. Has anyone worked with this algorithm before? Any good results?

Also: has anyone found (or made) an implementation of this CorEx algorithm in R yet?

submitted by /u/cleverchimp
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.