Clustering basicaly is a tool to help in an exploratoy analysis. There are another aproaches that can help you to investigate graphs.

One approach from NLP (Natural Language Processing) world is called embedding (https://en.m.wikipedia.org/wiki/Word_embedding). You can use some techniques to represent your graph in a vector space like: https://github.com/guoji-fu/Event2vec

This technique is particularly good if your graph is big and has a stochastic nature.

In python you can use this libraries to work with graphs. https://networkx.org/documentation/stable/tutorial.html

And this to sample graphs: https://brandonrozek.com/blog/networkx-random-sample-graph/ https://little-ball-of-fur.readthedocs.io/en/latest/index.html

others references: https://en.m.wikipedia.org/wiki/Graph_embedding https://link.medium.com/rW0beBuz1tb