Heterogeneous Graph Convolutional Network-Based Dynamic Rumor Detection on Social Media

Table 3

Experimental results of rumor detection on Twitter15/Twitter16. (NR: nonrumor; FR: false rumor; TR: true rumor; UR: unverified rumor).

Method	Acc.	NR	FR	TR	UR
		(a) Twitter15 dataset
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
TD-RvNN	0.723	0.682	0.758	0.821	0.654
Rumor2vec	0.796	0.883	0.746	0.836	0.723
ESODE	0.824	0.778	0.834	0.888	0.789
HDGCN	0.834	0.853	0.868	0.859	0.823
(b) Twitter16 dataset
DTC	0.473	0.254	0.080	0.190	0.482
RFC	0.585	0.752	0.415	0.547	0.563
SVM-TS	0.574	0.755	0.420	0.571	0.526
SVM-HK	0.511	0.648	0.434	0.473	0.451
GRU-RNN	0.633	0.617	0.715	0.577	0.527
BU-RvNN	0.718	0.723	0.712	0.779	0.659
TD-RvNN	0.737	0.662	0.743	0.835	0.708
Rumor2vec	0.852	0.857	0.769	0.927	0.850
ESODE	0.851	0.771	0.856	0.927	0.857
HDGCN	0.865	0.820	0.863	0.930	0.863