NIHRIO at SemEval-2018 Task 3: A Simple and Accurate Neural Network Model for Irony Detection in Twitter

Thanh Vu, Dat Quoc Nguyen, Xuan-Son Vu, Dai Quoc Nguyen, Michael Catt, Michael Trenell


Abstract
This paper describes our NIHRIO system for SemEval-2018 Task 3 “Irony detection in English tweets.” We propose to use a simple neural network architecture of Multilayer Perceptron with various types of input features including: lexical, syntactic, semantic and polarity features. Our system achieves very high performance in both subtasks of binary and multi-class irony detection in tweets. In particular, we rank at least fourth using the accuracy metric and sixth using the F1 metric. Our code is available at: https://github.com/NIHRIO/IronyDetectionInTwitter
Anthology ID:
S18-1085
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:
525–530
Language:
URL:
https://www.aclweb.org/anthology/S18-1085
DOI:
10.18653/v1/S18-1085
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1085.pdf