ECNU at SemEval-2018 Task 3: Exploration on Irony Detection from Tweets via Machine Learning and Deep Learning Methods

Zhenghang Yin, Feixiang Wang, Man Lan, Wenting Wang


Abstract
The paper describes our submissions to task 3 in SemEval-2018. There are two subtasks: Subtask A is a binary classification task to determine whether a tweet is ironic, and Subtask B is a fine-grained classification task including four classes. To address them, we explored supervised machine learning method alone and in combination with neural networks.
Anthology ID:
S18-1098
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:
600–606
Language:
URL:
https://www.aclweb.org/anthology/S18-1098
DOI:
10.18653/v1/S18-1098
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1098.pdf