RF-GNN: Random Forest Boosted Graph Neural Network for Social Bot Detection

Understand

The presence of a large number of bots on social media leads to adverse effects.

• Although Random forest algorithm is widely used in bot detection and can significantly enhance the performance of weak classifiers, it cannot utilize the interaction between accounts.
• This paper proposes a Random Forest boosted Graph Neural Network for social bot detection, called RF-GNN, which employs graph neural networks (GNNs) as the base classifiers to construct a random forest, effectively combining the advantages of ensemble learning and GNNs to improve the accuracy and robustness of the model.
• Specifically, different subgraphs are constructed as different training sets through node sampling, feature selection, and edge dropout.