Hidden Persuasion: Detecting Manipulative Narratives on Social Media During the 2022 Russian Invasion of Ukraine
This work addresses the problem of identifying manipulation techniques on social media for Ukrainian Telegram users, but it is incremental as it builds on existing models and shared task frameworks.
The paper tackled the problem of detecting manipulative narratives on social media during the 2022 Russian invasion of Ukraine by developing a system that achieved 2nd place in classification and 3rd place in span detection in the UNLP 2025 Shared Task.
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.