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arXiv Computation and Language By Sebastian Kula

Multilingual Models for Check-Worthy Social Media Posts Detection

Read the original on arXiv Computation and Language →

The paper reports a comprehensive study of transformer-based NLP models for detecting check-worthy social media posts, covering data collection, preprocessing, architecture selection, fine‑tuning, testing, and implementation. It focuses on multilingual models that can process English and low‑resource languages such as Arabic, Bulgarian, Dutch, Polish, Czech, and Slovak, and compares their performance to state‑of‑the‑art baselines. The work introduces multi‑label multilingual classifiers that simultaneously identify harmful content and posts containing verifiable factual claims efficiently.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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