Community detection algorithms

There seems to be a dearth of community detection algorithms in the current Graphs.jl. Hopefully this can be remedied in the future, and to that end I thought I'd list the ones that NetworkX currently has for comparison:

• Kernighan–Lin bipartition
• K-Clique (already in Graphs.jl as clique percolation)
• Greedy modular communities
• Lukes exact optimal weighted tree partitioning
• Label propagation (already in Graphs.jl)
• Leiden Community Detection
• Fluid Communities
• Girvan–Newman (@leerosenthalj still up for this?)
• Spectral clustering (in https://github.com/JuliaGraphs/CommunityDetection.jl)

There are also some in iGraphs that I think would be worth having:

• Louvain Community Detection
• Walktrap (short random walks)
• Spin-glass model and simulated annealing
• Optimal modularity
• Edge betweenness
• Eigenvector of the modularity matrix

The issue names no implementation files or tests; begin with the NetworkX community-algorithms reference and the listed iGraphs algorithms, then compare them with Graphs.jl and CommunityDetection.jl. Done would require narrowing this wishlist to a specific algorithm and defining its implementation and validation scope.