Fig. 4

Sensitivity analyses showing the correlation between true node centrality and estimated node centrality depends on the underlying network type being sampled and the type of egocentric sampling used. We simulated 15 replicates of each network type (scale-free and small-world) across a range of network sizes \(\left(5 \times {10}^{4},7.5\times {10}^{4},1\times {10}^{5},1.25\times {10}^{5},1.5\times {10}^{5}\right)\) all with mean node degree of 10. We then simulated the process of three types of egocentric sampling (ego_0, ego_1, and ego_2) and calculated the correlation of estimated centrality with true centrality. The black line indicates no correlation between sampled node statistics and true node statistics and the red triangle shows the mean across all replicates. Since we assumed perfect recall, we calculated the correlation in sampled degree on all nodes in the sampled network (i.e., not just the ego). Betweenness of egos was estimated from simulated networks by capping the number of search algorithm of shortest paths to 25