Model | Accuracy | Precision (%) | Recall (%) | F1-Score (%) | AUC (%) |
---|---|---|---|---|---|
LR | 83.1 ± 1.78 | 37.6 ± 1.16 | 82.1 ± 1.32 | 51.6 ± 1.54 | 89.9 ± 1.20 |
SVM | 81.6 ± 0.89 | 34.8 ± 0.77 | 77.6 ± 0.13 | 48.0 ± 0.64 | 87.6 ± 0.41 |
\(\mathit{ANN}_{\mathrm{text}+\mathrm{user}}\) | 84.1 ± 2.58 | 40.6 ± 2.39 | 75.7 ± 2.14 | 51.7 ± 3.21 | 88.2 ± 2.45 |
\(\mathit{ANN}_{\mathrm{text}+\mathrm{user}+\mathrm{network}}\) | 87.2 ± 2.02 | 45.3 ± 2.47 | 68.8 ± 2.05 | 54.2 ± 3.08 | 87.2 ± 1.72 |
\(\mathit{GraphSAGE}_{\mathrm{maxpool}}\) | 84.2 ± 1.59 | 40.3 ± 1.46 | 80.9 ± 1.08 | 53.4 ± 1.16 | 90.2 ± 1.34 |
\(\mathit{GraphSAGE}_{\mathrm{attention}}\) | 84.8 ± 1.11 | 40.6 ± 1.25 | 82.3 ± 1.18 | 54.3 ± 1.14 | 90.8 ± 1.07 |
\(\mathit{GraphSAGE}_{\mathrm{meanagg}}\) | 87.4 ± 1.04 | 46.1 ± 1.15 | 76.8 ± 1.11 | 57.5 ± 1.12 | 90.8 ± 1.03 |