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I2C at SemEval-2022 Task 6: Intended Sarcasm Detection on Social Networks with Deep Learning

Year: 2022

Type: conference-paper

Abstract: In this paper we present our approach and system description on iSarcasmEval: a SemEval task for intended sarcasm detection on social networks.This derives from our participation in SubTask A: Given a text, determine whether it is sarcastic or non-sarcastic.In our approach to complete the task, a comparison of several machine learning and deep learning algorithms using two datasets was conducted.The model which obtained the highest values of F1-score was a BERT-base-cased model.With this one, an F1-score of 0.2451 for the sarcastic class in the evaluation process was achieved.Finally, our team reached the 30 th position.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/2022.semeval-1.122

Authors: Pablo Gonzalez Diaz, Pablo Cordon, Jacinto Mata, Victoria Pachón

Institution: Universidad de Huelva

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4287887076

FWCI: 0.138

Cites: 12

Cited by: 1

Related to: 10