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Pseudo-labelling Enhanced Media Bias Detection

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 نشر من قبل Qin Ruan
 تاريخ النشر 2021
  مجال البحث الهندسة المعلوماتية
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Leveraging unlabelled data through weak or distant supervision is a compelling approach to developing more effective text classification models. This paper proposes a simple but effective data augmentation method, which leverages the idea of pseudo-labelling to select samples from noisy distant supervision annotation datasets. The result shows that the proposed method improves the accuracy of biased news detection models.


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