Table 3 The results of comparative experiments on the Twitter15 dataset.
From: TRGCN: a hybrid framework for social network rumor detection
Method | Acc | NR F1 | FR F1 | TR F1 | UR F1 |
|---|---|---|---|---|---|
DTC | 0.454 | 0.733 | 0.355 | 0.317 | 0.415 |
RFC | 0.565 | 0.810 | 0.422 | 0.401 | 0.543 |
SVM-TS | 0.544 | 0.796 | 0.472 | 0.404 | 0.483 |
SVM-HK | 0.493 | 0.650 | 0.439 | 0.342 | 0.336 |
GRU-RNN | 0.641 | 0.684 | 0.634 | 0.688 | 0.571 |
BU-RVNN | 0.708 | 0.695 | 0.728 | 0.759 | 0.653 |
Rumor2vec | 0.796 | 0.883 | 0.746 | 0.836 | 0.723 |
HDGCN | 0.834 | 0.853 | 0.868 | 0.859 | 0.823 |
GCRES | 0.853 | 0.855 | 0.858 | 0.903 | 0.746 |
GT-Base | 0.822 | 0.768 | 0.837 | 0.832 | 0.834 |
Bert-TRGCN | 0.333 | 0.415 | 0.306 | 0.275 | 0.311 |
TRGCN | 0.894 | 0.857 | 0.889 | 0.923 | 0.900 |