What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks

Understand

Graph homophily refers to the phenomenon that connected nodes tend to share similar characteristics.

• Understanding this concept and its related metrics is crucial for designing effective Graph Neural Networks (GNNs).
• The most widely used homophily metrics, such as edge or node homophily, quantify such "similarity" as label consistency across the graph topology.
• These metrics are believed to be able to reflect the performance of GNNs, especially on node-level tasks.