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Deploying Sentiment Predictor - BERT

Sentiment analysisSentimentDeploymentBERTTwitter
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VersionWorkflow created with KAP v5.4Latest, created on 
Mar 25, 2025 11:49 PM
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Deploying a Sentiment Analysis Predictive Model - BERT

This workflow applies a BERT model, trained over a Kaggle Dataset, on unlabeled social media posts to predict their sentiment. The last component visualizes (1) a bar chart with the number of negative/positive/neutral posts, (2) a word cloud of randomly selected posts, and (3) a table with all collected posts.

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.

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Used extensions & nodes

Created with KNIME Analytics Platform version 5.3.3
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.3.3

    knime profile image
    knime
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    KNIME JavaScript ViewsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.3.0

    knime profile image
    knime
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    KNIME JavasnippetTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.3.3

    knime profile image
    knime
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    KNIME Personal Productivity ToolsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.3.3

    knime profile image
    knime
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    Redfield BERT Nodes

    Redfield AB

    Version 1.0.3

    redfield

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