Table 9.
AUC results of big datasets of online social networks
| Methods/datasets | BK | DB | EPN | GWL | LMC |
|---|---|---|---|---|---|
| CN | 0.8194 | 0.5978 | 0.8685 | 0.8837 | 0.7826 |
| Salton | 0.8565 | 0.6059 | 0.9131 | 0.8972 | 0.7634 |
| JI | 0.8216 | 0.5999 | 0.8607 | 0.8775 | 0.7781 |
| Sorens | 0.8217 | 0.5797 | 0.8609 | 0.8773 | 0.7795 |
| HPI | 0.8542 | 0.6214 | 0.9012 | 0.8901 | 0.7783 |
| HDI | 0.8186 | 0.5830 | 0.8620 | 0.8775 | 0.7774 |
| LLHN | 0.8569 | 0.6163 | 0.9088 | 0.8907 | 0.7653 |
| AA | 0.8205 | 0.5886 | 0.8709 | 0.8801 | 0.7829 |
| RA | 0.8197 | 0.5879 | 0.8716 | 0.8806 | 0.7812 |
| PA | 0.8312 | 0.6691 | 0.8901 | 0.8674 | 0.9215 |
| LNBCN | 0.8201 | 0.5877 | 0.8725 | 0.8761 | 0.7903 |
| LNBAA | 0.8193 | 0.5874 | 0.8707 | 0.8757 | 0.7899 |
| LNBRA | 0.6400 | 0.5876 | 0.8724 | 0.8760 | 0.7886 |
| DeepWalk | 0.6426 | 0.5437 | 0.6028 | 0.6514 | 0.5386 |
| Node2vec | 0.9731 | 0.9714 | 0.9269 | 0.9794 | 0.8239 |
| Struc2vec | 0.9783 | 0.9796 | 0.9298 | 0.9852 | 0.8315 |
| GCN | 0.6563 | 0.6047 | 0.7937 | – | – |
| DGCNN | 0.9276 | 0.9444 | 0.9520 | 0.9419 | 0.9298 |
| LINE | 0.8383 | 0.6234 | 0.6454 | 0.8098 | 0.6875 |
| SDNE | 0.9705 | 0.9685 | 0.9193 | 0.9718 | 0.8197 |
| VERSE | 0.9969 | 0.9970 | 0.9964 | 0.9980 | 0.9865 |