欧洲大型研究机构电子邮件网络，转化为无向网络，并去除自边、孤立节点
Reference: Yin, H., Austin, R., Benson, J. L. & David, F. G. Local higher-order graph clustering. In Proceedings of the 23rd ACM SIGKDD
International Conference on Knowledge Discovery and Data Mining. 555–564 (ACM Press, 2017).
| Source | Target | Value |
|---|
| Group | Size | Nodes |
|---|
N and E are the number of nodes and links. 〈k〉 and 〈d〉 are the average degree and the average distance, respectively. C and r are the average clustering coefficient and the assortative coefficient. H is the degree heterogeneity. βc is the epidemic threshold of the SIR model.
| N | 986 |
|---|---|
| E | 16064 |
| <k> | 32.5842 |
| <d> | 2.5869 |
| <C> | 0.4071 |
| r | -0.0257 |
| H | 2.2912 |
| beta_c | 0.0136 |
Communities:
Modularity (Q):
Runtime (s):
AUC:
Precision:
Recall Rate:
F-value:
Accuracy: