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Structural Topic Modelling (STM) via Verified Components

StmStructural topic modelingTopicVerified componentTopic modeling
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Versionv1.0Latest, created on 
Jan 29, 2025 10:10 PM
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This example shows how to adopt the verified components Topic Extractor (STM) and the Topic Assigner (STM). The main difference with using the Topic Extractor (Parallel LDA) node is that also the document metadata can be provided during training. The component adopts the R library 'stm' and requires you to install conda to automatically install the R and the required libraries. Find more info about the R library, the KNIME R Integration and the Verified Components documentation in the links below.

External resources

  • “PoliBlogs08” data set by Eisenstein and Xing 2010
  • An Introduction to the Structural Topic Model (STM)
  • stm: R Package for Structural Topic Models - Roberts, Stewart and Tingley, Journal of Statistical Software (2019)
  • R Installation Guide - KNIME Docs
  • Miniconda Download and Installation - Conda Docs
  • Topic Assigner (STM) - KNIME Community Hub
  • Topic Extractor (STM) - KNIME Community Hub
  • Verified Component project - knime.com
  • Verified Components project - knime.com
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Created with KNIME Analytics Platform version 4.7.4
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