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Detection of Satiric News on Social Media: Analysis of the Phenomenon with a French Dataset
Publicatietype: In proceedings
Citatie:
Boektitel: The 28th International Conference on Computer Communications and Networks (ICCCN 2019)
Jaar: 2019
Maand: July
Uitgever: IEEE
Locatie: Valencia, Spain
ISSN: 2637-9430
ISBN: 978-1-7281-1856-7
URL: https://ieeexplore.ieee.org/do...
DOI: 10.1109/ICCCN.2019.8847041
Samenvatting: The topic of deceptive and satiric news has drawn attention from both the public and the academic community, as such misinformation has the potential to have extremely adverse effects on individuals and society. Detecting false and satiric news automatically is a challenging problem in deception detection, and it has tremendous real-word political and social influences. In this paper, we contribute a useful French satiric dataset to the research community and provide a satiric news detection system using machine learning to automate classifications significantly. In addition, we present the preliminary results of our research designed to discriminate real news from satiric stories, and thus ultimately reduce false and satiric news distribution.
Trefwoorden: Classification, fake news, French dataset, machine learning, media, news satire, social media
Auteurs Liu, Zhan
Shabani, Shaban
Glassey Balet, Nicole
Maria, Sokhn
Toegevoegd door: []
Totaalscore: 0
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  • Liu et al._ICCCN_2019.pdf
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