Every once in a while I have a network related data science type problem to muddle through and I invariably want to try visualise some aspect of it, so I invariably try use Gephi for it, and it invariably leads to a frustrating experience for anything non trivial, and so I invariably end up doing it in code + graphviz instead.

To be fair, a large part of the problem is that many graph-related algorithms are simply very expensive (computationally). For example, many layouts (especially classical ones such as Fruchterman-Rheingold) are very slow. That often makes visualization frustrating when you have more than a couple of hundred nodes and/or a dense network. And we should acknowledge that the Gephi people have put a lot of work into making it work.

So network analysis evidently benefits from think-then-do approaches, while exploratory work is really hard.

And here is the book link: https://link.springer.com/book/10.1007/978-3-7091-0741-6