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Topic Models from reviews

Marketing AnalyticsRegressionR scriptLDANLP
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VersionVersion created in KAP v5.4Latest, created on 
Mar 25, 2025 10:47 PM
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Topic Models from Reviews

This workflow addresses the problem of extracting and modeling topics from reviews.

Block 1 performs the data preparation on review texts. Block 2 optimizes the parameters for the LDA algorithm. Block 3 applies the LDA algorithm with optimized parameters and displays the LDA topic probabilities along with the average number of stars by topic. Block 4 estimates the importance of topics via linear regression (KNIME) and polynomial regression (R).

If you use this workflow, please cite:
F. Villaroel Ordenes & R. Silipo, “Machine learning for marketing on the KNIME Hub: The development of a live repository for marketing applications”, Journal of Business Research 137(1):393-410, DOI: 10.1016/j.jbusres.2021.08.036.

External resources

  • 10.1016/j.jbusres.2021.08.036
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Used extensions & nodes

Created with KNIME Analytics Platform version 5.4.0
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    knime
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    KNIME Excel SupportTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    knime
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    KNIME Interactive R Statistics IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    knime
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    KNIME JavaScript ViewsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    KNIME JavasnippetTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    knime
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    KNIME Math Expression (JEP)Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    knime
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    KNIME TextprocessingTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    knime

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