jsLDA is a free, open source tool for corpus-based in browser topic modelling. Users can test the tool via the provided demo, or download the source code to run on their own system. Users can load any corpus accessible from a URL, and can train the tool on the topics within the corpus via the iteration function. Once jsLDA has been trained to the user's satisfaction, documents can be sorted according to topic and explored based on topic correlations.
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jsLDA was used in this research abstract available in XML formal here https://raw.githubusercontent.com/lehkost/ToolXtractor/master/data/xml/2019/HOOVER_David_L__The_Prepare_and_Visualize_Mallet_Data_Spread.xml