A Report on the 2020 Sarcasm Detection Shared Task

• URL: http://arxiv.org/abs/2005.05814v2
• Date: Thu, 4 Jun 2020 20:31:11 GMT
• Title: A Report on the 2020 Sarcasm Detection Shared Task
• Authors: Debanjan Ghosh and Avijit Vajpayee and Smaranda Muresan
• Abstract summary: Sarcasm analysis is a popular research problem in natural language processing. As the community working on computational approaches for sarcasm detection is growing, it is imperative to analyze the current state-of-the-art. We report on the shared task on sarcasm detection we conducted as a part of the 2nd Workshop on Figurative Language Processing (Fig 2020) at ACL 2020.
• Score: 30.430371267812554
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Detecting sarcasm and verbal irony is critical for understanding people's actual sentiments and beliefs. Thus, the field of sarcasm analysis has become a popular research problem in natural language processing. As the community working on computational approaches for sarcasm detection is growing, it is imperative to conduct benchmarking studies to analyze the current state-of-the-art, facilitating progress in this area. We report on the shared task on sarcasm detection we conducted as a part of the 2nd Workshop on Figurative Language Processing (FigLang 2020) at ACL 2020.

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