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

Jason Angel, Segun Taofeek Aroyehun, Alexander Gelbukh

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaSemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop
EditoresGuy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
EditorialAssociation for Computational Linguistics (ACL)
Páginas951-955
Número de páginas5
ISBN (versión digital)9781955917803
EstadoPublicada - 2022
Evento16th International Workshop on Semantic Evaluation, SemEval 2022 - Seattle, Estados Unidos
Duración: 14 jul. 202215 jul. 2022

Serie de la publicación

NombreSemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop

Conferencia

Conferencia16th International Workshop on Semantic Evaluation, SemEval 2022
País/TerritorioEstados Unidos
CiudadSeattle
Período14/07/2215/07/22

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