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Deploying a Sentiment Analysis Predictive Model - Supervised Machine Learning

Sentiment analysis Sentiment Machine learning SVM Deployment
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This worflow applies an SVM model, trained on the Kaggle Dataset (https://www.kaggle.com/crowdflower/twitter-airline-sentiment), on new tweets around #xxx to predict their sentiment. The last component visualizes: 1. the bar chart with the number of negative/positive/neutral tweets; 2. the word cloud of all collected tweets; 3. the table with all collected tweets. Selecting a word in the word cloud selects the corresponding tweets the word in contained into.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.6.3
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.2

    knime
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    KNIME Ensemble Learning Wrappers Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    knime
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    KNIME Excel Support Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.2

    knime
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    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.2

    knime
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    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    knime
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    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    knime
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    KNIME Textprocessing Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.2

    knime
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    KNIME Twitter Connectors Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    knime
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