Building a Sentiment Analysis Predictive Model - Supervised Machine Learning
This workflow uses a Kaggle Dataset (https://www.kaggle.com/crowdflower/twitter-airline-sentiment) including thousands of customer social media posts towards six US airlines. Contributors annotated the valence of the tweets as positive, negative and 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.