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Detecting fake news in tweets from text and propagation graph: IRISA's participation to the FakeNews task at MediaEval 2020

Vincent Claveau 1
1 LinkMedia - Creating and exploiting explicit links between multimedia fragments
IRISA-D6 - MEDIA ET INTERACTIONS, Inria Rennes – Bretagne Atlantique
Abstract : This paper presents the participation of IRISA to the task of fake news detection from tweets, relying either on the text or on propagation information. For the text based detection, variants of BERT-based classification are proposed. In order to improve this standard approach, we investigate the interest of augmenting the dataset by creating tweets with fine-tuned generative models. For the graph based detection, we have proposed models characterizing the propagation of the news or the users' reputation.
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https://hal.archives-ouvertes.fr/hal-03116027
Contributor : Vincent Claveau Connect in order to contact the contributor
Submitted on : Wednesday, January 20, 2021 - 8:57:23 AM
Last modification on : Wednesday, November 3, 2021 - 8:07:49 AM
Long-term archiving on: : Wednesday, April 21, 2021 - 6:09:07 PM

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  • HAL Id : hal-03116027, version 1

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Vincent Claveau. Detecting fake news in tweets from text and propagation graph: IRISA's participation to the FakeNews task at MediaEval 2020. MediaEval 2020 - MediaEval Benchmarking Initiative for Multimedia Evaluation, Dec 2020, online, United States. pp.1-3. ⟨hal-03116027⟩

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