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.
CITATION STYLE
Nikhil, N., & Srivastava, M. M. (2018). Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection. In NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop (pp. 628–632). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s18-1102
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