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The corpus comprises the output of 9 publishers in a week close to the US elections. Among the selected publishers are 6 prolific hyperpartisan ones (three left-wing and three right-wing), and three mainstream publishers (see Table 1). All publishers earned Facebook’s blue checkmark, indicating authenticity and an elevated status within the network. For seven weekdays (September 19 to 23 and September 26 and 27), every post and linked news article of the 9 publishers was fact-checked by professional journalists at BuzzFeed. In total, 1,627 articles were checked, 826 mainstream, 256 left-wing and 545 right-wing. The imbalance between categories results from differing publication frequencies.
{"references": ["Martin Potthast, Johannes Kiesel, Kevin Reinartz, Janek Bevendorff, and Benno Stein. A Stylometric Inquiry into Hyperpartisan and Fake News. In 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018), pages 231-240, July 2018. Association for Computational Linguistics."]}
Fake News, Hyperpartisan News, News, News articles
Fake News, Hyperpartisan News, News, News articles
| 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). | 2 | |
| 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. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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| downloads | 138 |

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