Table 5 Bot classification performance summary for the Italian-Election dataset
From: Detecting bots in social-networks using node and structural embeddings
Feature-Set | Accuracy | Precision | Recall | f1-Score | MCC |
|---|---|---|---|---|---|
Node Features | 0.66 | 0.65 | 0.66 | 0.66 | 0.31 |
All Embeddings | 0.69 | 0.70 | 0.64 | 0.67 | 0.38 |
Node2Vec | 0.61 | 0.62 | 0.57 | 0.59 | 0.22 |
DeepWalk | 0.62 | 0.62 | 0.59 | 0.60 | 0.23 |
LSME | 0.64 | 0.64 | 0.65 | 0.64 | 0.29 |
Struc2Vec | 0.63 | 0.66 | 0.55 | 0.60 | 0.27 |
GraphWave | 0.64 | 0.65 | 0.61 | 0.63 | 0.29 |
Role2Vec | 0.67 | 0.68 | 0.61 | 0.65 | 0.34 |