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
摘要
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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引用它的顶会 Paper2
- Spectrum Tuning: Post-Training for Distributional Coverage and In-Context SteerabilityTaylor Sorensen, Benjamin Newman, Jared Moore, Chan Young Park 等ICLR 2026 · 被引用 19 次
- PERSEVAL: A Framework for Perspectivist Classification EvaluationSoda Marem Lo, Silvia Casola, Erhan Sezerer, Valerio Basile 等EMNLP 2025
它引用的顶会 Paper7
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- EPIC: Multi-Perspective Annotation of a Corpus of IronySimona Frenda, Alessandro Pedrani, Valerio Basile, Soda Marem Lo 等ACL 2023 · 被引用 9 次
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