Hi all, I have run into a runtime/complexity question where I am wondering if someone can give me insights into why this might happen. I have conducted the following steps: 1.) Create some random network 2.) Calculate eigenvector centrality 3.) Sample 10% random nodes 4.) Filter graph by nodes 5.) Calculate eigenvector centrality on sample I have observed that for the sample, the eigenvector centrality calculation takes much longer, in some cases (dependent e.g., on block structure) it takes way longer (like 30 times longer). I am now trying to figure out why this is the case. I assume it has something to do with the convergence which might be probably because links are missing in the sample. If I do the same for e.g., PageRank the difference is not that drastic (it still takes longer in the sample). Does anyone have an idea what is going on here? Thanks, Philipp