Papers by Dominik Bär
HQP: A Human-Annotated Dataset for Detecting Online Propaganda (2024.findings-acl)
Copied to clipboard
| Challenge: | Existing datasets for detecting online propaganda use weak labels that can be noisy and incorrect. |
| Approach: | They propose a dataset for detecting online propaganda with high-quality labels . they show that state-of-the-art language models fail in detecting propaganda when trained with weak labels compared to prompt-based learning . |
| Outcome: | The proposed dataset is the first large-scale dataset for detecting online propaganda that was created through human annotation. |