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This paper describes our system submitted to SemEval-2019 Task 4: Hyperpartisan News Detection. We focus on removing the inherent noise in the hyperpartisanship dataset from both data-level and model-level by leveraging semi-supervised pseudo-labels and the stateof-the-art BERT model. Our model achieves 75.8% accuracy in the final by-article dataset without ensemble learning.
Lee et al. (Tue,) studied this question.
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