IMO the order of papers should be, although i realise this may be a bit too much looking back

• start off with spectral graph papers and the label propogation papers such as zhu 2003 zhou 2004.
• then the spectral convolution papers such as defferrard 2016.
• then the gcn paper and maybe the gat paper and how powerful are graph nns.

From there you are well set up to pick your poison on which type of graph ml to focus on. Dynamic vs static, hetro vs homo etc.

Some cool people to follow (i dont know much about the social media stuff)

Bronstein at twitter, petar velickovic at deep mind, xavier bresson, william hamilton. Sure there are loads more

Pytorch geometric and dgl have loads of good docs for practical examples.