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
Venues:
SemEval | *SEM
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
628–632
Language:
URL:
https://aclanthology.org/S18-1102
DOI:
10.18653/v1/S18-1102
Bibkey:
Cite (ACL):
Nishant Nikhil and Muktabh Mayank Srivastava. 2018. Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 628–632, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection (Nikhil & Mayank Srivastava, SemEval-*SEM 2018)
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https://preview.aclanthology.org/ingestion-script-update/S18-1102.pdf
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