Podlab at SemEval-2019 Task 3: The Importance of Being Shallow
Andrew Nguyen, Tobin South, Nigel Geoffrey Bean, Jonathan Tuke, Lewis Mitchell · 2019
This paper describes our linear SVM system for emotion classification from conversational dialogue, entered in SemEval2019 Task 3. We used off-the-shelf tools coupled with feature engineering and parameter tuning to create a simple, interpretable, yet high-performing, classification model.Our system achieves a micro F1 score of 0.7357, which is 92% of the top score for the competition, demonstrating that "shallow" classification approaches can perform well when coupled with detailed feature selection and statistical analysis.