Fig. 2

GNN accuracy for homophilic datasets. This figure presents the accuracy of GNN models on the homophilic datasets (original and manipulated). The red dashed line represents the median accuracy of the feature-only baseline. The performance on the original graphs is consistently higher than that of the baseline. Increasing homophily results in a higher accuracy for all datasets. Decreasing community mixing causes a performance drop, which still outperforms the baseline in most cases. Increasing mixing (by destroying sub-communities) while preserving homophily generally causes an increase in performance. Destroying homophily and community structure (with \(Hom^-\)) causes a major performance drop