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  5. FakeClaim: A Multiple Platform-Driven Dataset for Identification of Fake News on 2023 Israel-Hamas War
 
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FakeClaim: A Multiple Platform-Driven Dataset for Identification of Fake News on 2023 Israel-Hamas War

Abstract
We contribute the first publicly available dataset of factual claims from different platforms and fake YouTube videos on the 2023 Israel-Hamas war for automatic fake YouTube video classification. The FakeClaim data is collected from 60 fact-checking organizations in 30 languages and enriched with metadata from the fact-checking organizations curated by trained journalists specialized in fact-checking. Further, we classify fake videos within the subset of YouTube videos using textual information and user comments. We used a pre-trained model to classify each video with different feature combinations. Our best-performing fine-tuned language model, Universal Sentence Encoder (USE), achieves a Macro F1 of 87%, which shows that the trained model can be helpful for debunking fake videos using the comments from the user discussion.
Publication Type
ConferencePaper
Author
Shahi, Gautam Kishore 
•
Jaiswal, Amit Kumar 
•
Mandl, Thomas 
Editor
Goharian, Nazli
•
He, Yulan
•
Lipani, Aldo
•
Macdonald, Craig
•
McDonald, Graham
•
Ounis, Iadh
•
Tonellotto, Nicola
Date Issued
2024
DOI
10.1007/978-3-031-56069-9_5
Faculty
Fachbereich 3 
Institute / Institution
Institut für Informationswissenschaft und Sprachtechnologie 
Published in
Advances in information retrieval: Proceedings - Part V
Conference
46. European Conference on Information Retrieval, Glasgow, 24.03.-28.03.2024
Publisher
Springer
Publisher Place
Cham
Page Start
66
Page End
74
Series Name
Lecture Notes in Computer Science
Issue Number
14612
ISBN
978-3-031-56068-2
978-3-031-56069-9
HilPub short link
https://hilpub.uni-hildesheim.de/handle/ubhi/18453
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