Building a Sentiment Analysis Predictive Model - Lexicon Based Approach
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. In the lexicon based approach, the number of words with a positive and a negative meaning are counted per post. Based on these numbers, a sentiment score is calculated and used to classify the 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.