@InProceedings{nikhil-mayanksrivastava:2018:S18-1,
  author    = {Nikhil, Nishant  and  Mayank Srivastava, Muktabh},
  title     = {Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection},
  booktitle = {Proceedings of The 12th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {628--632},
  abstract  = {In this paper, we describe the system submitted for the SemEval 2018 Task 3 (Irony detection in English tweets) Subtask A by the team Binarizer. Irony detection is a key task for many natural language processing works. Our method treats ironical tweets to consist of smaller parts containing different emotions. We break down tweets into separate phrases using a dependency parser. We then embed those phrases using an LSTM-based neural network model which is pre-trained to predict emoticons for tweets. Finally, we train a fully-connected network to achieve classification.},
  url       = {http://www.aclweb.org/anthology/S18-1102}
}