Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection

Nishant Nikhil, Muktabh Mayank Srivastava


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.
Anthology ID:
S18-1102
Volume:
Proceedings of The 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
628–632
Language:
URL:
https://www.aclweb.org/anthology/S18-1102
DOI:
10.18653/v1/S18-1102
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1102.pdf