conference-paper Open access

SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and Arabic

  • Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Research footprint

At a glance

Citations
93
References
58
Comments
0
Paper overview

Abstract

iSarcasmEval is the first shared task to target intended sarcasm detection: the data for this task was provided and labelled by the authors of the texts themselves. Such an approach minimises the downfalls of other methods to collect sarcasm data, which rely on distant supervision or third-party annotations. The shared task contains two languages, English and Arabic, and three subtasks: sarcasm detection, sarcasm category classification, and pairwise sarcasm identification given a sarcastic sentence and its non-sarcastic rephrase. The task received submissions from 60 different teams, with the sarcasm detection task being the most popular. Most of the participating teams utilised pre-trained language models. In this paper, we provide an overview of the task, data, and participating teams.

Record transparency

Publication details

DOI
10.18653/v1/2022.semeval-1.111
OpenAlex
W4287888944
Document type
conference-paper
Language
EN
Source
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Last metadata update
Community

Comments

Log in to join the discussion.

  1. No comments yet. Start the discussion.