NIHRIO at SemEval-2018 Task 3: A Simple and Accurate Neural Network Model for Irony Detection in Twitter
Computation and Language
2018-04-10 v2
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 third using the accuracy metric and fifth using the F1 metric. Our code is available at https://github.com/NIHRIO/IronyDetectionInTwitter
Keywords
Cite
@article{arxiv.1804.00520,
title = {NIHRIO at SemEval-2018 Task 3: A Simple and Accurate Neural Network Model for Irony Detection in Twitter},
author = {Thanh Vu and Dat Quoc Nguyen and Xuan-Son Vu and Dai Quoc Nguyen and Michael Catt and Michael Trenell},
journal= {arXiv preprint arXiv:1804.00520},
year = {2018}
}
Comments
In proceedings of the 12th International Workshop on Semantic Evaluation, SemEval 2018, to appear (6 pages, 2 figures)