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This repository is a research prototype for early detecting fake news shared in social media when evidence or metadata is not present.

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ECOL - Fake News Detection Framework for the Healthcare Domain

framework More details are given in our paper.

scripts folder has examples for reproducing the study:

  • scripts/elasticsearch_ops.sh is used for extracting relevant past fake news
  • scripts/links_ops.sh is used for extracting link information on the posts
  • scripts/train_server.sh is used for training the components of the ECOL

Trained models and processed data can be downloaded from this link.

Datasets

The list of additional datasets for training/testing some of the components of the framework: FakeHealth NELA-2019

Citation

Please use the following citation if you use our code:

@chapter{baris2021ecol,
      title={ECOL: Early Detection of COVID Lies Using Content, Prior Knowledge and Source Information}, 
      author={Ipek Baris and Zeyd Boukhers},
      year={2021},
      book={Combating Online Hostile Posts in Regional Languages during Emergency Situation },
      publisher={Springer International Publishing},
}

Preprint version of the paper is publicly available.

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This repository is a research prototype for early detecting fake news shared in social media when evidence or metadata is not present.

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