Building Sentiment Predictor - Deep Learning

<p><strong>Building a Sentiment Analysis Predictor - Deep Learning using an RNN-LSTM</strong><br><br>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 tweet into positive, negative and neutral. Once users are satisfied with the model evaluation, they should export 1) Dictionary, 2) Category to Number Model, 3) Trained Network for deployment in non-annotated data. <br><br>Reference: <br>F. Villaroel Ordenes &amp; 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.</p>