Bot Detection on Cresci Shortcut 2015 (test)
96.7Accuracy/F1 ScoreShortcut_tr
Evaluation Results
| Method | Links | |
|---|---|---|
| Shortcut_trBackbone Model=BotRGCN, Feature Category=Topics2025.11 | 96.7 | |
| Dataset-Level*Backbone Model=BotRGCN, Feature Category=Emotions2025.11 | 95.6 | |
| Text-Level*Backbone Model=BotRGCN, Feature Category=Emotions2025.11 | 95.1 | |
| Dataset-Level*Backbone Model=BotRGCN, Feature Category=Topics2025.11 | 95.1 | |
| Model-Level*Backbone Model=BotRGCN, Feature Category=Emotions2025.11 | 94.6 | |
| Text-Level*Backbone Model=BotRGCN, Feature Category=Topics2025.11 | 93.8 | |
| Shortcut_trBackbone Model=BotRGCN, Feature Category=Emotions2025.11 | 90.3 | |
| Model-Level*Backbone Model=BotRGCN, Feature Category=Topics2025.11 | 90 | |
| Model-Level*Backbone Model=BotRGCN, Feature Category=Sentiments2025.11 | 89 | |
| Text-Level*Backbone Model=BotRGCN, Feature Category=Sentiments2025.11 | 88.5 | |
| Dataset-Level*Backbone Model=BotRGCN, Feature Category=Sentiments2025.11 | 87.7 | |
| Model-Level*Backbone Model=BotRGCN, Feature Category=Values2025.11 | 82.3 | |
| Shortcut_trBackbone Model=BotRGCN, Feature Category=Values2025.11 | 81.5 | |
| Dataset-Level*Backbone Model=BotRGCN, Feature Category=Values2025.11 | 78.7 | |
| AMR+CIGABackbone Model=BotRGCN, Feature Category=Topics2025.11 | 77.4 | |
| AMR+CIGABackbone Model=BotRGCN, Feature Category=Emotions2025.11 | 77 | |
| Text-Level*Backbone Model=BotRGCN, Feature Category=Values2025.11 | 76.9 | |
| Shortcut_trBackbone Model=BotRGCN, Feature Category=Sentiments2025.11 | 74.9 | |
| AMR+CIGABackbone Model=BotRGCN, Feature Category=Sentiments2025.11 | 67.8 | |
| AMR+CIGABackbone Model=BotRGCN, Feature Category=Values2025.11 | 59.2 |