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Erschienen in:
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2024 | OriginalPaper | Buchkapitel

UCoD: Ensemble BERT for Hierarchical Classification of the Urdu Disinformation Corpus

verfasst von : Umar Farooq, Omer Beg, Faisal Riaz, Saeid Jamali, William Holderbaum, Umar Raza

Erschienen in: The Second International Adaptive and Sustainable Science, Engineering and Technology Conference

Verlag: Springer Nature Switzerland

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Abstract

Online disinformation poses a growing threat, requiring fact-checking and detection/prevention measures. To address this, we propose a hierarchical classification approach using the DistilBERT and XLM-RoBERTa ensemble architectures on the Urdu Corpus of Disinformation (UCoD). Our ensemble outperforms other models like RNNs, LSTMs, k-nearest neighbors, random forests, and quadratic discriminant analysis, achieving a weighted F1 of 68.7 on UCoD. These results confirm the advantage of ensembles for imbalanced corpora, supporting the use of deep learning techniques in combating disinformation.

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Metadaten
Titel
UCoD: Ensemble BERT for Hierarchical Classification of the Urdu Disinformation Corpus
verfasst von
Umar Farooq
Omer Beg
Faisal Riaz
Saeid Jamali
William Holderbaum
Umar Raza
Copyright-Jahr
2024
Buch
The Second International Adaptive and Sustainable Science, Engineering and Technology Conference

Print ISBN: 978-3-031-53934-3

Electronic ISBN: 978-3-031-53935-0

Copyright-Jahr: 2024

DOI
https://doi.org/10.1007/978-3-031-53935-0_25

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