Journal of Big Data

Table 4 Results of comparison with different models on twitter16 datasets

From: KAGN:knowledge-powered attention and graph convolutional networks for social media rumor detection

Method	Acc	NR	FR	TR	UR
Method	Acc	F_1	F_1	F_1	F_1
DTC	0.465	0.643	0.393	0.419	0.403
RFC	0.585	0.752	0.415	0.547	0.563
SVM-TS	0.574	0.755	0.42	0.571	0.526
PTK	0.732	0.74	0.709	0.836	0.686
GRU	0.633	0.772	0.489	0.686	0.593
BU-RvNN	0.718	0.723	0.712	0.779	0.659
TD-RvNN	0.737	0.662	0.743	0.835	0.708
PPC	0.863	0.82	0.898	0.843	0.837
Bi-GCN	0.88	0.847	0.869	0.937	0.865
KAGN	0.901	0.864	0.881	0.946	0.908

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