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This dataset is provided to facilitate reproducibility of results presented in the following paper: Chengcheng Shao, Pik-Mai Hui, Lei Wang, Xinwen Jiang, Alessandro Flammini, Filippo Menczer and Giovanni Luca Ciampaglia (2018): Anatomy of an online misinformation network. Preprint arXiv:1801.06122, arxiv.org/abs/1801.06122 Please read carefully both the paper and the README file attached to understand what is contained in this dataset before proceeding. These data are provided for non-commercial purposes only. If you use this dataset for research, please be sure to cite the above preprint, or preferably the final published version that will be shown on the arXiv.
C.S. was supported by the China Scholarship Council. X.J. was supported in part by the National Natural Science Foundation of China (No. 61272010). G.L.C. was supported by IUNI. A.F. and F.M. were supported in part by the James S. McDonnell Foundation (grant 220020274) and the National Science Foundation (award CCF-1101743). The funders had no role in data collection or decision to publish.
Twitter, Misinformation, Fact Checking, Hoaxy, Social Media
Twitter, Misinformation, Fact Checking, Hoaxy, Social Media
| 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 | 114 | |
| downloads | 10 |

Views provided by UsageCounts
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