By the way if you want to explore network science but don't really know where to start, consider Gephi (currently being refactored, and just updated a few days ago) or Cytoscape (if you're more drawn to bioinformatics).

Both make it easy to load/generate standard datasets, import tabular data, and have a good selection of plugins. It's easy to kick stuff out to either from NetworkX using /gefx or graphml, and you'll be able to experiment with a wide variety of layout algorithms and metrics. If you don't find the toy/benchmark networks intuitive, considering hitting the HN API for your source material; it's a lot easier to grasp the topic by studying relationships that are already familiar.

Do you have any advice/ideas about ways to learn about graph layout algorithms themselves, including dynamic/real-time algorithms (which allow for user interaction)? I have been skimming through various papers and the first book on this page [0], in particular the chapter on force directed algorithms, because they seem to be the earliest and most general graph drawing methods.

[0] http://graphdrawing.org/books.html

You mean algos related only to NetworkX or in general? If you are looking for NetworkX related stuff besides the official docs, NetworkX Guide [1] is a good starting point.

[1] https://networkx.guide/

In general! Graph drawing and interactivity is an interesting problem in my opinion.

Maybe this will be interesting to you. An open source graph visualization library called Orb.[1] There is a series of blog post that talk about the development and reasoning behind this library. [2]

[1] https://github.com/memgraph/orb

[2] https://memgraph.com/blog?topics=Orb#list