PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent
Liu, Jiateng Ai, Lin Liu, Zizhou Karisani, Payam Hui, Zheng Fung, Yi Nakov, Preslav Hirschberg, Julia Ji, Heng
Liu, Jiateng
Ai, Lin
Liu, Zizhou
Karisani, Payam
Hui, Zheng
Fung, Yi
Nakov, Preslav
Hirschberg, Julia
Ji, Heng
Supervisor
Department
Natural Language Processing
Embargo End Date
Type
Conference proceeding
Date
2025
License
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
Propaganda plays a critical role in shaping public opinion and fueling disinformation. While existing research primarily focuses on identifying propaganda techniques, it lacks the ability to capture the broader motives and the impacts of such content. To address these challenges, we introduce PropaInsight, a conceptual framework grounded in foundational social science research, which systematically dissects propaganda into techniques, arousal appeals, and underlying intent. PropaInsight offers a more granular understanding of how propaganda operates across different contexts. Additionally, we present PropaGaze, a novel dataset that combines human-annotated data with high-quality synthetic data generated through a meticulously designed pipeline. Our experiments show that off-the-shelf LLMs struggle with propaganda analysis, but training with PropaGaze significantly improves performance. Fine-tuned Llama-7B-Chat achieves 203.4% higher text span IoU in technique identification and 66.2% higher BertScore in appeal analysis compared to 1-shot GPT-4-Turbo. Moreover, PropaGaze complements limited human-annotated data in data-sparse and cross-domain scenarios, showing its potential for comprehensive and generalizable propaganda analysis.
Citation
J. Liu et al., “PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent,” Proceedings - International Conference on Computational Linguistics, COLING, vol. Part, pp. 5607–5628, Jan. 2025.
Source
Proceedings - International Conference on Computational Linguistics, COLING
Conference
Keywords
PropaInsight, Underlying intent, PropaInsight framework
Subjects
Source
Publisher
Association for Computational Linguistics