Document Type

Conference Proceeding

Publication Title

Proceedings of the Annual Meeting of the Association for Computational Linguistics


We present a new multilingual multifacet dataset of news articles, each annotated for genre (objective news reporting vs. opinion vs. satire), framing (what key aspects are highlighted), and persuasion techniques (logical fallacies, emotional appeals, ad hominem attacks, etc.). The persuasion techniques are annotated at the span level, using a taxonomy of 23 fine-grained techniques grouped into 6 coarse categories. The dataset contains 1,612 news articles covering recent news on current topics of public interest in six European languages (English, French, German, Italian, Polish, and Russian), with more than 37k annotated spans of persuasion techniques. We describe the dataset and the annotation process, and we report the evaluation results of multilabel classification experiments using state-of-the-art multilingual transformers at different levels of granularity: token-level, sentence-level, paragraph-level, and document-level.

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Computational linguistics, European languages, Evaluation results, Fine grained, Multi-label classifications, News articles, News reporting, On currents, On-currents, Online news, Public interest


Open Access

Archived thanks to ACL Anthology

License: CC BY 4.0 DEED

Uploaded: 22 February 2024