As a news addict, I love seeing how politics can garner such emotive responses across social media and wondered if this anecdotal sense of passion could translate into machine learning classification. I found a dataset of Tweets made in reaction to the first Republican Presidential debate in 2016 (here ) and wanted to create a three level sentiment classifier that could interpret emotions from the text of the Tweets. This article is part of a suite of methodologies and techniques I put together, for now I will just be focusing on one aspect; the humble Support Vector Machine. As a secondary task, I noticed the dataset was severely imbalanced so wanted to try and upsample the minority classes in an effort to improve the usefulness of the classifier across all labels (this will hopefully help the classifier improve across all categories).

#data-science #machine-learning #twitter #classification-algorithms #python