Deploying Sentiment Predictor - BERT

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.