It's painful because (IMHO) the H index is just a much worse approximation of something that we could actually achieve with PageRank for academic citations. In that case, a bunch of middling papers would be rewarded, but so too would one critical paper that lays a foundation for a field.
Think of an army randomly moving through your citation graph; the more particularly nodes are trampled over, the more pagerank it has.
Now: if this army is informed about the shortest routes and instead moves about optimally, the most-trampled over places have higher betweenness centrality. I'd like my simulated citing scientist to be smart.
I'll give you a bonus: the Louvain algorithm for community detection. Whatever ships with Networkx, Gephi, etc. doesn't work for my (correlation-derived, pruned with graphical lasso) networks, but the Louvain method (a greedy approximation to modularity maximization; the real math magic is in the concept of modularity and the configuration model) is awesome.
I always thought that PageRank was inspired on methods previously used for scoring academic papers. Now I'm wondering if I misunderstood something, or my professor misunderstood it first. Damn.
PageRank has nothing to do with h-index to my knowledge. The problem with using PageRank-like methods for academic papers is that academic papers mostly reference backwards in time (except for the occasional draft or work-in-progress being referenced, but proper cycles are rare). A triangular matrix doesn't yield an interesting stationary distribution...
I don't know if it makes any difference, but if PageRank should replace the h-index, the most direct equivalent would be to rank the authors rather than the papers, no?
