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

April 02, 2018 · Entered Twilight · 🏛 International Workshop on Semantic Evaluation

"Last commit was 7.0 years ago (≥5 year threshold)"

Evidence collected by the PWNC Scanner

Repo contents: .gitignore, data, description, readme.md, requirements.txt, src

Authors Thanh Vu, Dat Quoc Nguyen, Xuan-Son Vu, Dai Quoc Nguyen, Michael Catt, Michael Trenell arXiv ID 1804.00520 Category cs.CL: Computation & Language Citations 24 Venue International Workshop on Semantic Evaluation Repository https://github.com/NIHRIO/IronyDetectionInTwitter ⭐ 25 Last Checked 1 month ago

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