Deploying a Sentiment Analysis Predictive Model - Supervised Machine Learning
This workflow applies an SVM model, trained on the Kaggle Dataset (https://www.kaggle.com/crowdflower/twitter-airline-sentiment), to predict sentiment on new tweets around the query "to:AmericanAir." This query retrieves tweets directed to American Airlines. 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. Selecting a word in the word cloud fetches its corresponding 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.
This workflow applies an SVM model, trained on the Kaggle Dataset (https://www.kaggle.com/crowdflower/twitter-airline-sentiment), to predict sentiment on new tweets around the query "to:AmericanAir." This query retrieves tweets directed to American Airlines. 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. Selecting a word in the word cloud fetches its corresponding 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.