Work

TUG-CIC at SemEval-2021 Task 6: Two-stage Fine-tuning for Intended Sarcasm Detection

Year: 2022

Type: conference-paper

Abstract: We present our systems and findings for the iSarcasmEval: Intended Sarcasm Detection In English and Arabic at SEMEVAL 2022.Specifically we take part in the Subtask A for the English language.The task aims to determine whether a text from social media (a tweet) is sarcastic or not.We model the problem using knowledge sources, a pre-trained language model on sentiment/emotion data and a dataset focused on intended sarcasm.Our submission ranked third place among 43 teams.In addition, we show a brief error analysis of our best model to investigate challenging examples for detecting sarcasm.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/2022.semeval-1.133

Authors: Jason Angel, Segun Aroyehun, Alexander Gelbukh

Institutions: Instituto Politécnico Nacional, Graz University of Technology

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Instituto Politécnico Nacional, Consejo Nacional de Ciencia y Tecnología

Awards: G3488607286, G6958583472