SaRoHead: A Dataset for Satire Detection in Romanian Multi-Domain News Headlines

• URL: http://arxiv.org/abs/2504.07612v1
• Date: Thu, 10 Apr 2025 10:03:29 GMT
• Title: SaRoHead: A Dataset for Satire Detection in Romanian Multi-Domain News Headlines
• Authors: Mihnea-Alexandru Vîrlan, Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel,
• Abstract summary: SaRoHead is the first corpus for satire detection in Romanian multi-domain news headlines.<n>Our findings show that the clickbait used in some non-satirical headlines significantly influences the model.
• Score: 1.6976911886883272
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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