Work

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

Year: 2018

Type: conference-paper

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.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/s18-1097

Authors: Delia Irazú Hernández Farías, Fernando Sánchez-Vega, Manuel Montes-y-Gómez, Paolo Rosso

Institutions: National Institute of Astrophysics, Optics and Electronics, Universitat Politècnica de València

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: Consejo Nacional de Ciencia y Tecnología

Award: G1893250317