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Third trial dataset for the SemEval 2019 Task 4: Hyperpartisan News Detection. The dataset contains 1 million articles. It is split in training (200,000 left, 400,000 least, 200,000 right) and validation (50,000 left, 100,000 least, 50,000 right), where no publisher that occurs in the training set also occurs in the validation set. All articles are labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com. The trial data is not fully cleaned. Due to some encoding error, some characters are replaced by question marks. However, all files are already fully compatible with the XML schema files.
Hyperpartisan, SemEval 2019, Hyperpartisanship, Hyperpartisan news, Biased news, News bias, SemEval 2019 Task 4, SemEval
Hyperpartisan, SemEval 2019, Hyperpartisanship, Hyperpartisan news, Biased news, News bias, SemEval 2019 Task 4, SemEval
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 58 | |
| downloads | 20 |

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