Modelling Persuasion through Misuse of Rhetorical Appeals

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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.

TitelNLP4PI 2022 - 2nd Workshop on NLP for Positive Impact, Proceedings of the Workshop
Antal sider12
ForlagAssociation for Computational Linguistics
Publikationsdatodec. 2022
AnsøgerAssociation for Computational Linguistic
ISBN (Trykt)978-1-959429-19-7
ISBN (Elektronisk)9781959429197
StatusUdgivet - dec. 2022
BegivenhedWorkshop on NLP for Positive Impact 2022 - Abu Dhabi
Varighed: 7 dec. 20227 dec. 2022


KonferenceWorkshop on NLP for Positive Impact 2022
ByAbu Dhabi


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