MultiPICo: Multilingual Perspectivist Irony Corpus
Silvia Casola, Simona Frenda, Soda Marem Lo, Erhan Sezerer, Antonio Uva, Valerio Basile, Cristina Bosco, Alessandro Pedrani, Chiara Rubagotti, Viviana Patti, Davide Bernardi
Abstract
Recently, several scholars have contributed to the growth of a new theoretical framework in NLP called perspectivism. This approach aims to leverage data annotated by different individuals to model diverse perspectives that affect their opinions on subjective phenomena such as irony. In this context, we propose MultiPICo, a multilingual perspectivist corpus of ironic short conversations in different languages and linguistic varieties extracted from Twitter and Reddit. The corpus includes sociodemographic information about its annotators. Our analysis of the annotated corpus shows how different demographic cohorts may significantly disagree on their annotation of irony and how certain cultural factors influence the perception of the phenomenon and the agreement on the annotation. Moreover, we show how disaggregated annotations and rich annotator metadata can be exploited to benchmark the ability of large language models to recognize irony, their positionality with respect to sociodemographic groups, and the efficacy of perspective-taking prompting for irony detection in multiple languages.
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Install the CLIlune papers fulltext f58e8da4-9cc5-4856-922a-579b23807041Cited by top-tier papers2
- Spectrum Tuning: Post-Training for Distributional Coverage and In-Context SteerabilityTaylor Sorensen, Benjamin Newman, Jared Moore, Chan Young Park et al.ICLR 2026 · 19 citations
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Builds on7
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- Social Chemistry 101: Learning to Reason about Social and Moral NormsMaxwell Forbes, Jena D. Hwang, Vered Shwartz, Maarten Sap et al.EMNLP 2020 · 11 citations
- EPIC: Multi-Perspective Annotation of a Corpus of IronySimona Frenda, Alessandro Pedrani, Valerio Basile, Soda Marem Lo et al.ACL 2023 · 9 citations
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