A Multi-Label Dataset of French Fake News: Human and Machine Insights

Benjamin Icard, François Maine, Morgane Casanova, Géraud Faye, Julien Chanson +4 more
3/24/2024
cs.CLcs.LG

Official code: obs-info/obsinfox (5 stars, last commit 2024-03-21).

Abstract

We present a corpus of 100 documents, OBSINFOX, selected from 17 sources of French press considered unreliable by expert agencies, annotated using 11 labels by 8 annotators. By collecting more labels than usual, by more annotators than is typically done, we can identify features that humans consider as characteristic of fake news, and compare them to the predictions of automated classifiers. We present a topic and genre analysis using Gate Cloud, indicative of the prevalence of satire-like text in the corpus. We then use the subjectivity analyzer VAGO, and a neural version of it, to clarify the link between ascriptions of the label Subjective and ascriptions of the label Fake News. The annotated dataset is available online at the following url: https://github.com/obs-info/obsinfox Keywords: Fake News, Multi-Labels, Subjectivity, Vagueness, Detail, Opinion, Exaggeration, French Press

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Code Implementations(1)

obs-info/obsinfoxOfficial100%

A Multi-Label Annotated Dataset of French Fake News

50Mar 11, 20242 years agoNOASSERTION

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Cite this paper

@article{icard2024multilabel,
  title  = {A Multi-Label Dataset of French Fake News: Human and Machine Insights},
  author = {Benjamin Icard and François Maine and Morgane Casanova and Géraud Faye and Julien Chanson and Guillaume Gadek and Ghislain Atemezing and François Bancilhon and Paul Égré},
  year   = {2024},
  eprint = {2403.16099},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.16099v2}
}

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