@inproceedings{kyslyi-etal-2025-unlp,
    title = "The {UNLP} 2025 Shared Task on Detecting Social Media Manipulation",
    author = "Kyslyi, Roman  and
      Romanyshyn, Nataliia  and
      Sydorskyi, Volodymyr",
    editor = "Romanyshyn, Mariana",
    booktitle = "Proceedings of the Fourth Ukrainian Natural Language Processing Workshop (UNLP 2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria (online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/acl25-workshop-ingestion/2025.unlp-1.12/",
    pages = "105--111",
    ISBN = "979-8-89176-269-5",
    abstract = "This paper presents the results of the UNLP 2025 Shared Task on Detecting Social Media Manipulation. The task included two tracks: Technique Classification and Span Identification. The benchmark dataset contains 9,557 posts from Ukrainian Telegram channels manually annotated by media experts. A total of 51 teams registered, 22 teams submitted systems, and 595 runs were evaluated on a hidden test set via Kaggle. Performance was measured with macro F1 for classification and token{-}level F1 for identification. The shared task provides the first publicly available benchmark for manipulation detection in Ukrainian social media and highlights promising directions for low{-}resource propaganda research. The Kaggle leaderboard is left open for further submissions."
}