LDAvis: Interactive Visualization of Topic Models by Carson Sievert and Kenny Shirley.
From the webpage:
Tools to create an interactive web-based visualization of a topic model that has been fit to a corpus of text data using Latent Dirichlet Allocation (LDA). Given the estimated parameters of the topic model, it computes various summary statistics as input to an interactive visualization built with D3.js that is accessed via a browser. The goal is to help users interpret the topics in their LDA topic model.
From the description:
This video (recorded September 2014) shows how interactive visualization is used to help interpret a topic model using LDAvis. LDAvis is an R package which extracts information from a topic model and creates a web-based visualization where users can interactively explore the model. More details, examples, and instructions for using LDAvis can be found here — https://github.com/cpsievert/LDAvis
Excellent exploration of a data set using LDAvis.
Will all due respect to “agile” programming, modeling before you understand a data set isn’t a winning proposition.