INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter

2018-06-01SEMEVAL 2018Unverified0· sign in to hype

Delia Iraz{\'u} Hern{\'a}ndez Far{\'\i}as, Fern S{\'a}nchez-Vega, o, Manuel Montes-y-G{\'o}mez, Paolo Rosso

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Abstract

This paper describes an ensemble approach to the SemEval-2018 Task 3. The proposed method is composed of two renowned methods in text classification together with a novel approach for capturing ironic content by exploiting a tailored lexicon for irony detection. We experimented with different ensemble settings. The obtained results show that our method has a good performance for detecting the presence of ironic content in Twitter.

Tasks

General Classification Sentiment Analysis text-classification Text Classification Word Embeddings

INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter

Abstract

Tasks

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