Table 2 Rumor detection results on Twitter15 datasets.

From: Heterogeneous graph convolutional network for rumor detection with multi-level interactive fusion and graph reconstruction

Method

Acc

NR

FR

TR

UR

\({F}_{1}\)

\({F}_{1}\)

\({F}_{1}\)

\({F}_{1}\)

DTC

0.454

0.733

0.355

0.317

0.415

SVM-TS

0.544

0.796

0.472

0.404

0.483

SVM-TK

0.667

0.619

0.669

0.772

0.645

MVAE

0.612

0.523

0.656

0.701

0.445

RvNN

0.723

0.682

0.758

0.821

0.654

PPC

0.842

0.818

0.875

0.811

0.790

GCAN

–

0.825

0.830

0.826

0.877

VAE-GCN

0.856

0.749

0.795

0.905

0.809

BI-GCN

0.886

0.891

0.860

0.930

0.864

GLAN

0.890

0.936

0.908

0.897

0.817

HGATRD

0.911

0.953

0.929

0.905

0.854

MLI-GRA

0.920

0.958

0.911

0.920

0.889

  1. (N: Non-Rumor; F: False Rumor; T: True Rumor; U: Unverified Rumor).