Datasets:

nlp-brin-id
/

unsup-content

Tasks:

Text Classification

Languages:

Indonesian

Size Categories:

10K<n<100K

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This dataset is taken from nlp-brin-id/id-hoax-report-merge-v2.
The subsets can be utilized as samples for unsupervised contrastive learning based on longer textual claim (content of the public report based on the corresponding title of the claim) as input for fake news detection.

Attributes used = 'Content'.

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Models trained or fine-tuned on nlp-brin-id/unsup-content

nlp-brin-id/simcse-fakenews-unsup-content-v1

Updated Mar 16 • 1

Collection including nlp-brin-id/unsup-content

Contrastive Learning for Fake News

Collection

Datasets and model for training models with contrastive loss. Domain/task: Fake news / hoax classification. • 15 items • Updated Apr 1