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Quality of a projected-hypergraph partition

Source: R/hypergraph_communities.R
hg_community_quality.Rd

Reports graph-partition diagnostics on the association projection: unweighted coverage, weighted coverage, performance, weighted modularity, and conductance. Conductance is the maximum (worst) community conductance \(cut(S, \bar S) / min(vol(S), vol(\bar S))\); lower is better.

Usage

hg_community_quality(
  hg,
  partition,
  method = c("association", "citation"),
  duplicate_edges = c("count", "collapse"),
  self_association = FALSE,
  edge_source = NULL
)

Arguments

hg

A static net_hg.

partition

An hg_communities() result, a tidy node/label table, or a named label vector.

method

The projection the partition is scored on: the "association" graph (default) or the undirected "citation" graph.

duplicate_edges, self_association, edge_source

Projection controls passed to hg_project(). Together these reproduce the paper's binary/multi and self-association representations.

Value

A one-row data frame.

References

Fortunato, S. (2010). Community detection in graphs. Physics Reports, 486(3-5), 75-174. doi:10.1016/j.physrep.2009.11.002

Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69, 026113. doi:10.1103/PhysRevE.69.026113

Coupette, C., Hartung, D., & Katz, D. M. (2024). Legal hypergraphs. Philosophical Transactions of the Royal Society A, 382, 20230141. doi:10.1098/rsta.2023.0141