Yeah, it was a pretty straightforward read. If he wants to chat the next time he is in town, let me know. Their paper is working from some of the same intuitions that I am working from, though my dataset is quite a bit richer. I mention this because there are opportunities that arise over larger networks than at the level of countries. For instance, they mention extensions to random graphs, which is fairly natural.
I didn’t quite get why they chose PageRank in particular, but I assume this will give them graphs that are nicely approximated by Barabási–Albert. I am still trying to find good ways of identifying which random graph best approximates mine. The particular problem that I am fleshing out has to do with recovering a best-fit Beltrami–Laplace operator so that I can more meaningfully recover a best-fit latent Riemannian manifold and associated cohomology.
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