2000 character limit reached
NIHRIO at SemEval-2018 Task 3: A Simple and Accurate Neural Network Model for Irony Detection in Twitter (1804.00520v2)
Published 2 Apr 2018 in cs.CL
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
- Thanh Vu (59 papers)
- Dat Quoc Nguyen (55 papers)
- Xuan-Son Vu (15 papers)
- Dai Quoc Nguyen (26 papers)
- Michael Catt (2 papers)
- Michael Trenell (1 paper)