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LDAvis: Interactive Visualization of Topic Models
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.
Getting started
Browse package contents
Package details |
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| Author | Carson Sievert [aut, cre], Kenny Shirley [aut] |
| Maintainer | Carson Sievert <cpsievert1@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.3.2 |
| URL | https://github.com/cpsievert/LDAvis |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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Try the LDAvis package in your browser
Any scripts or data that you put into this service are public.
