Unsupervised Fake News Detection on Social Media: A Generative Approach

@inproceedings{Yang2019UnsupervisedFN,
  title={Unsupervised Fake News Detection on Social Media: A Generative Approach},
  author={Shuo Yang and Kai Shu and Suhang Wang and Renjie Gu and Fan Wu and Huan Liu},
  booktitle={AAAI},
  year={2019}
}
Social media has become one of the main channels for people to access and consume news, due to the rapidness and low cost of news dissemination on it. [] Key Method We treat truths of news and users’ credibility as latent random variables, and exploit users’ engagements on social media to identify their opinions towards the authenticity of news. We leverage a Bayesian network model to capture the conditional dependencies among the truths of news, the users’ opinions, and the users’ credibility.

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