Pseudo-labelling Enhanced Media Bias Detection
University College Dublin（都柏林大学学院）；Insight Centre for Data Analytics（洞察数据分析中心）
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
