• Corpus ID: 38266719

Neural Stance Detectors for Fake News Challenge

@inproceedings{Zeng2017NeuralSD,
  title={Neural Stance Detectors for Fake News Challenge},
  author={Qingguo Zeng},
  year={2017}
}
Fake news pose serious threat to our society nowadays, particularly due to its wide spread through social networks. While human fact checkers cannot handle such tremendous information online in real time, AI technology can be leveraged to automate fake news detection. The first step leading to a sophisticated fake news detection system is the stance detection between statement and body text. In this work, we analyze the dataset from Fake News Challenge (FNC1) and explore several neural stance… 
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11 Citations
Background Citations
3
Results Citations
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