Hi,
Sorry, I do not monitor so much igraph ML these days. Thanks to twitter, Nick points me this topic.
Good remarks.
I get back into this and indeed it seems false to say that Infomap (in igraph) do not work with isolated vertices (=degree zero).
By the way, this was true with Walktrap, but I just discover that it is no more the case :
https://github.com/igraph/igraph/commit/3465b4e60c587a412ae175a3f70a0f486613bf93
Infomap use random walks with "teleportation", thus isolated nodes (= degree zero) or disconnected components do not cause convergence issue (or other math problem).
And I do not remember implementation tricks that may raise issue with isolated nodes.
I also run it on some test graphs (with isolated nodes) it just work perfectly...
So I should say that I don't know why I wrote that in the documentation...
I do not have historical versions of my work (this was done before igraph mv to git and I lost my local bzr) so unfortunately I can't make archeology to better understand it. (maybe just a wrong copy from Walktrap documentation)
However for large networks it may be an optimization to run infomap on each disconnected components (isolated nodes are trival disconnected components). Indeed disconnected components are clearly largest possible communities, and so it is not necessary for Infomap to deal (= compute random walks) with the entire graph. However as greedy optimization in infomap "follow" the links to seek communities, i'm not sure this will really change anything in term of time complexity...