R package 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.
Keywords for this software
References in zbMATH (referenced in 6 articles )
Showing results 1 to 6 of 6.
- Chung-hong Chan; Marius Sältzer: oolong: An R package for validating automated content analysis tools (2020) not zbMATH
- Harshvardhan, G. M.; Gourisaria, Mahendra Kumar; Pandey, Manjusha; Rautaray, Siddharth Swarup: A comprehensive survey and analysis of generative models in machine learning (2020)
- Margaret Roberts; Brandon Stewart; Dustin Tingley: stm: An R Package for Structural Topic Models (2019) not zbMATH
- Mair, Patrick: Modern psychometrics with R (2018)
- Ruffini, Matteo; Casanellas, Marta; Gavaldà, Ricard: A new method of moments for latent variable models (2018)
- Azqueta-Gavaldón, Andrés: Developing news-based economic policy uncertainty index with unsupervised machine learning (2017)