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

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          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.

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          Multilayer feedforward networks are universal approximators

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            Support vector machines

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              Ridge Estimators in Logistic Regression

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                Journal
                02 April 2018
                Article
                1804.00520
                9fe0692d-e217-4eaa-b5c2-bdc4d8ff7ba2

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                In proceedings of the 12th International Workshop on Semantic Evaluation, SemEval 2018, to appear (6 pages, 2 figures)
                cs.CL

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