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A Survey in Automatic Irony Processing: Linguistic, Cognitive, and Multi-X Perspectives

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arxiv 2209.04712 v1 pith:R63WEOVK submitted 2022-09-10 cs.CL

Qingcheng Zeng , An-Ran Li This is my paper · ORCID
classification cs.CL
keywords ironyprocessingcognitivelinguisticautomaticcomputationallanguagemulti-x
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Irony is a ubiquitous figurative language in daily communication. Previously, many researchers have approached irony from linguistic, cognitive science, and computational aspects. Recently, some progress have been witnessed in automatic irony processing due to the rapid development in deep neural models in natural language processing (NLP). In this paper, we will provide a comprehensive overview of computational irony, insights from linguistic theory and cognitive science, as well as its interactions with downstream NLP tasks and newly proposed multi-X irony processing perspectives.

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Cited by 1 Pith paper

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  1. Irony Detection, Reasoning and Understanding in Zero-shot Learning

    cs.CL 2025-01 conditional novelty 5.0 of 10

    A multi-prompt framework that asks LLMs to generate irony knowledge improves zero-shot irony detection, reasoning, and understanding on six datasets.

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