@inproceedings{akhynko-etal-2025-hidden,
    title = "Hidden Persuasion: Detecting Manipulative Narratives on Social Media During the 2022 {R}ussian Invasion of {U}kraine",
    author = "Akhynko, Kateryna  and
      Kosovan, Oleksandr  and
      Trokhymovych, Mykola",
    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-1.19/",
    pages = "194--202",
    ISBN = "979-8-89176-269-5",
    abstract = "This paper presents one of the top-performing solutions to the UNLP 2025 Shared Task on Detecting Manipulation in Social Media. The task focuses on detecting and classifying rhetorical and stylistic manipulation techniques used to influence Ukrainian Telegram users. For the classification subtask, we fine-tuned the Gemma 2 language model with LoRA adapters and applied a second-level classifier leveraging meta-features and threshold optimization. For span detection, we employed an XLM-RoBERTa model trained for multi-target, including token binary classification. Our approach achieved 2nd place in classification and 3rd place in span detection."
}