Propaganda Detection
Propaganda detection is a natural-language-processing task that automatically identifies and labels persuasion and manipulation techniques in text — such as loaded language, oversimplified solutions, bandwagon appeals, and glittering generalities. It builds on the fine-grained propaganda analysis introduced by Da San Martino et al. (2019), turning rhetorical manipulation into structured, technique-level labels.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Da San Martino, G. et al. (2019). Fine-Grained Analysis of Propaganda in News Articles. EMNLP. · DOI 10.18653/v1/D19-1565
- Rashkin, H. et al. (2017). Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking. EMNLP. · DOI 10.18653/v1/D17-1317
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.