Abstract
Our system for the PropEval task explores the ability of semantic features to detect and label propagandistic rhetorical techniques in English news articles. For Subtask 2, labeling identified propagandistic fragments with one of fourteen technique labels, our system attains a micro-averaged F1 of 0.40; in this paper, we take a detailed look at the fourteen labels and how well our semantically-focused model detects each of them. We also propose strategies to fill the gaps.- Anthology ID:
- 2020.semeval-1.243
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 1847–1852
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.243
- DOI:
- 10.18653/v1/2020.semeval-1.243
- Cite (ACL):
- Maia Petee and Alexis Palmer. 2020. UNTLing at SemEval-2020 Task 11: Detection of Propaganda Techniques in English News Articles. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1847–1852, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- UNTLing at SemEval-2020 Task 11: Detection of Propaganda Techniques in English News Articles (Petee & Palmer, SemEval 2020)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/2020.semeval-1.243.pdf