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Communication Dans Un Congrès Année : 2021

LUX (Linguistic aspects Under eXamination): Discourse Analysis for Automatic Fake News Classification

Lucas Azevedo
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Brian Davis
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Manel Zarrouk

Résumé

The democratization/decentralization of both the production and consumption of information has resulted in a subjective and often misleading depiction of facts known as Fake News-a phenomenon that is effectively shaping the perception of reality for many individuals. Manual fact-checking is time-consuming and cannot scale and although automatic factchecking, vis a vis machine learning holds promise, it is significantly hindered by a deficit of suitable training data. We present both a novel dataset, VERITAS(VERIfying Textual Aspects), a collection of fact-checked claims, containing their original documents and LUX(Language Under eXamination), a text classifier that makes use of an extensive linguistic analysis to infer the likelihood of the input being a piece of fake-news.
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Dates et versions

hal-03659147 , version 1 (04-05-2022)

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Lucas Azevedo, Mathieu D’aquin, Brian Davis, Manel Zarrouk. LUX (Linguistic aspects Under eXamination): Discourse Analysis for Automatic Fake News Classification. The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Aug 2021, Online, France. pp.41-56, ⟨10.18653/v1/2021.findings-acl.4⟩. ⟨hal-03659147⟩
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