k_core: Generalized k-core

In anespinosa/netmem: Social Network Measures using Matrices

Generalized k-core

Description

Generalized k-core for undirected, directed, weighted and multilevel networks

Usage

k_core(
  A,
  B1 = NULL,
  multilevel = FALSE,
  type = "in",
  digraph = FALSE,
  loops = FALSE,
  weighted = FALSE,
  alpha = 1
)

Arguments

A	A matrix object.
B1	An incidence matrix for multilevel networks.
multilevel	Whether the measure of k-core is for multilevel networks.
type	Character string, “out” (outdegree), “in” (indegree) and “all” (degree)
digraph	Whether the matrix is directed or undirected
loops	Whether the diagonal of the matrix is considered or not
weighted	Whether the measure of k-core is for valued matrices
alpha	Sets the alpha parameter in the generalised measures from Opsahl et al. (2010)

Value

This function return the k-core.

Author(s)

Alejandro Espinosa-Rada

References

Batagelj, V., & Zaveršnik, M. (2011). Fast algorithms for determining (generalized) core groups in social networks. Advances in Data Analysis and Classification, 5(2), 129–145. https://doi.org/10.1007/s11634-010-0079-y

Eidsaa, M., & Almaas, E. (2013). s-core network decomposition: A generalization of $k$-core analysis to weighted networks. Physical Review E, 88(6), 062819. https://doi.org/10.1103/PhysRevE.88.062819

Seidman S (1983). 'Network structure and minimum degree'. Social Networks, 5, 269-287.

Examples

A1 <- matrix(c(
  0, 1, 0, 0, 0,
  1, 0, 0, 1, 0,
  0, 0, 0, 1, 0,
  0, 1, 1, 0, 1,
  0, 0, 0, 1, 0
), byrow = TRUE, ncol = 5)
B1 <- matrix(c(
  1, 0, 0,
  1, 1, 0,
  0, 1, 0,
  0, 1, 0,
  0, 1, 1
), byrow = TRUE, ncol = 3)

k_core(A1, B1, multilevel = TRUE)

anespinosa/netmem documentation built on April 5, 2025, 5:02 p.m.