@InProceedings{nguyen-EtAl:2019:S19-2,
  author    = {Nguyen, Andrew  and  South, Tobin  and  Bean, Nigel  and  Tuke, Jonathan  and  Mitchell, Lewis},
  title     = {Podlab at SemEval-2019 Task 3: The Importance of Being Shallow},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {292--296},
  abstract  = {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 fea- ture selection and statistical analysis.},
  url       = {http://www.aclweb.org/anthology/S19-2050}
}