Hidden Persuasion: Detecting Manipulative Narratives on Social Media During the 2022 Russian Invasion of Ukraine
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Abstract (arXiv)
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.
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References · 9
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- 2020SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articlescited by 80
- 2021WikiCheck: An end-to-end open source Automatic Fact-Checking API based on Wikipediacited by 12
- 2023LLM-RM at SemEval-2023 Task 2: Multilingual Complex NER using XLM-RoBERTacited by 7
- 2024An Open Multilingual System for Scoring Readability of Wikipediacited by 7
- 2024From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representationcited by 6
- 2025Characterizing Knowledge Manipulation in a Russian Wikipedia Forkcited by 1
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