The University of Sheffield
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Trained RPDNN LOO-CV models for early rumor detection

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posted on 2021-01-18, 12:16 authored by Jie Gao, Sooji Han, Xingyi SongXingyi Song
This is the release of our RPDNN trained LOO-CV model for early rumor detection.

Dataset * contains our trained RPDNN models that is developed to predict social media rumor in early stage.

The purpose of this release is for research only and for reproducing our results in the paper.

For how to load and use the model, please our Allennlp and Pytorch based source code via

For more details, please read our paper:

Gao. J., Han S., Song X., Ciravegna, F. (2020). “RP-DNN: A Tweet level propagation context based deep neural networks for early rumor detection in Social Media”, In: The LREC 2020 Proceedings. The International Conference on Language Resources and Evaluation, 11-16 May 2020, Marseille. LREC 2020.



  • There is no personal data or any that requires ethical approval


  • The data complies with the institution and funders' policies on access and sharing

Sharing and access restrictions

  • The data can be shared openly

Data description

  • The file formats are open or commonly used

Methodology, headings and units

  • Headings and units are explained in the files
  • There is a readme.txt file describing the methodology, headings and units