Towards an Ontology for Propaganda Detection in News Articles

Author ORCID Identifier

0000-0003-0809-0664

Document Type

Conference Paper

Disciplines

Computer Sciences

Publication Details

Lecture Notes in Computer Science ((LNISA,volume 12739))

The Semantic Web: ESWC 2021 Satellite Events(ESWC 2021)

https://link.springer.com/chapter/10.1007/978-3-030-80418-3_35

doi:10.1007/978-3-030-80418-3_35

Abstract

The proliferation of mis/disinformation in the media has had a profound impact on social discourse and politics in the United States. Some argue that democracy itself is threatened by the lies, chicanery, and flimflam - in short, propaganda - emanating from the highest pulpits, podiums, and soapboxes in the land. Propaganda differs from mis/disinformation in that it need not be false, but instead, it relies on rhetorical devices which aim to manipulate the audience into a particular belief or behavior. While falsehoods can be debunked, albeit with disputable efficacy, beliefs are harder to cut through. The detection of “Fake News” has received a lot of attention recently with some impressive results, however, propaganda detection remains challenging. This proposal aims to further the research into propaganda detection by constructing an ontology with this specific goal in mind, while drawing from multiple disciplines within Computer Science and the Social Sciences.

DOI

10.1007/978-3-030-80418-3_35

Funder

Science Foundation Ireland

Creative Commons License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.

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