Datasets
Standard Dataset
fakenews
- Citation Author(s):
- Submitted by:
- Quan-Hui Liu
- Last updated:
- Mon, 09/02/2024 - 21:34
- DOI:
- 10.21227/rer7-8a33
- Data Format:
- License:
95 Views- Categories:
- Keywords:
Abstract
The dataset1 includes fake&real news propagation networks on Twitter built according to fact-check information and the news retweet graphs were originally extracted by [FakeNewsNet](https://github.com/KaiDMML/FakeNewsNet).The statistics of the dataset is shown below:| Data | #Graphs | #Total Nodes | #Total Edges | #Avg. Nodes per Graph ||-------|--------|--------|--------|--------|| Politifact | 314 | 41,054 | 40,740 | 131 || Gossipcop | 5464 | 314,262 | 308,798 | 58 |. And the dataset2 is the Chinese Weibo datase, the dataset information is shown as below:# of Users 2,746,818# of Source tweets 4664# of Posts 3,805,656# of False rumors 2313# of True rumors 2351Avg. time length / tree 2,460.7 HoursAvg. # of posts / tree 816Max # of posts / tree 59,318Min # of posts / tree 10
For dataset1, you can directly use the .npz/.npy files for experiments. For dataset2, handle the feature files and document the relationship between each node. Also, store the feature matrix for each node. Lastly, save all the information into a file in '.npy' format.
Dataset Files
- dataset1 data.zip (101.44 MB)
- dataset2 Weibo.zip (47.79 MB)
