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  • Building Sentiment Predictor --Solution
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Building a Sentiment Analysis Predictive Model - Supervised Machine Learning

Sentiment analysis Sentiment Machine learning SVM Supervised learning
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This workflow uses a Kaggle Dataset including 14K customer tweets towards six US airlines (https://www.kaggle.com/crowdflower/twitter-airline-sentiment). Contributors annotated the valence of the tweets as positive, negative or neutral. Once users are satisfied with the model evaluation, they should export (1) the Vector Space and (2) the Trained Model for deployment over non-annotated data. 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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Created with KNIME Analytics Platform version 4.5.1
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    KNIME Weka Data Mining Integration (3.7) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

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