arXiv:2504.07612
SaRoHead: A Dataset for Satire Detection in Romanian Multi-Domain News Headlines
원문 초록
The headline is an important part of a news article, influenced by expressiveness and connection to the exposed subject. Although most news outlets aim to present reality objectively, some publications prefer a humorous approach in which stylistic elements of satire, irony, and sarcasm blend to cover specific topics. Satire detection can be difficult because a headline aims to expose the main idea behind a news article. In this paper, we propose SaRoHead, the first corpus for satire detection in Romanian multi-domain news headlines. Our findings show that the clickbait used in some non-satirical headlines significantly influences the model.
함께 살펴볼 논문
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Make Satire Boring Again: Reducing Stylistic Bias of Satirical Corpus by Utilizing Generative LLMs
SaRoCo: Detecting Satire in a Novel Romanian Corpus of News Articles
FreSaDa: A French Satire Data Set for Cross-Domain Satire Detection
A Multi-Modal Method for Satire Detection using Textual and Visual Cues
MuSaRoNews: A Multidomain, Multimodal Satire Dataset from Romanian News Articles
Comparison of Multilingual and Bilingual Models for Satirical News Detection of Arabic and English
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