FakeClaim: A Multiple Platform-driven Dataset for Identification of Fake News on 2023 Israel-Hamas War
CoRR(2024)
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. The dataset is
available on Github[https://github.com/Gautamshahi/FakeClaim]
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