Modelling Persuasion through Misuse of Rhetorical Appeals

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review


It is important to understand how people use words to persuade each other. This helps understand debate, and detect persuasive narratives in regard to e.g. misinformation. While computational modelling of some aspects of persuasion has received some attention, a way to unify and describe the overall phenomenon of when persuasion becomes undesired and problematic, is missing. In this paper, we attempt to address this by proposing a taxonomy of computational persuasion. Drawing upon existing research and resources, this paper shows how to re-frame and re-organise current work into a coherent framework targeting the misuse of rhetorical appeals. As a study to validate these re-framings, we then train and evaluate models of persuasion adapted to our taxonomy. Our results show an application of our taxonomy, and we are able to detecting misuse of rhetorical appeals, finding that these are more often used in misinformative contexts than in true ones.

Original languageEnglish
Title of host publicationNLP4PI 2022 - 2nd Workshop on NLP for Positive Impact, Proceedings of the Workshop
Number of pages12
PublisherAssociation for Computational Linguistics
Publication dateDec 2022
Commissioning bodyAssociation for Computational Linguistic
ISBN (Print)978-1-959429-19-7
ISBN (Electronic)9781959429197
Publication statusPublished - Dec 2022
EventWorkshop on NLP for Positive Impact 2022 - Abu Dhabi
Duration: 7 Dec 20227 Dec 2022


ConferenceWorkshop on NLP for Positive Impact 2022
CityAbu Dhabi


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