SCRF Analytics and Tag Mining?
In my day job, I do text analysis with an unsupervised learning algorithm called “topic models.” These models basically take texts and allow you to cluster them automatically. After clustering them you can discover latent topics contained within the texts and label those topics appropriately. The model can also automatically assign labels to texts.
I was thinking: would you all be interested in having me run all the SCRF posts through a topic model to see what kind of new labels/tags might emerge? The cool thing about this is that once the code is written, you can continuously estimate new models to discover new tags and, at least in theory, automatically apply those tags proactively and retroactively.
Also topic models have some cool plots associated w/ them that can be posted on SCRF. Here’s an example of one such plot using tweets: https://alexisperrier.com/assets/LDA_topic_7.png. The bubbles represent how many documents fall into a topic and the distance between them represents how similar they are in terms of keywords.