This workflow applies a BERT model, trained over a 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, and (3) the table with all collected tweets. 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.
Used extensions & nodes
Created with KNIME Analytics Platform version 4.5.2
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