These functions return logical vectors the length of the ties in a network identifying which hold certain properties or positions in the network.

  • tie_is_triangular() marks ties that are in triangles.

  • tie_is_cyclical() marks ties that are in cycles.

  • tie_is_transitive() marks ties that complete transitive closure.

  • tie_is_triplet() marks ties that are in a transitive triplet.

  • tie_is_simmelian() marks ties that are both in a triangle and fully reciprocated.

They are most useful in highlighting parts of the network that are cohesively connected.

tie_is_triangular(.data)

tie_is_transitive(.data)

tie_is_triplet(.data)

tie_is_cyclical(.data)

tie_is_simmelian(.data)

tie_is_forbidden(.data)

tie_is_imbalanced(.data)

Arguments

.data

An object of a manynet-consistent class:

  • matrix (adjacency or incidence) from {base} R

  • edgelist, a data frame from {base} R or tibble from {tibble}

  • igraph, from the {igraph} package

  • network, from the {network} package

  • tbl_graph, from the {tidygraph} package

Examples

ison_monks %>% to_uniplex("like") %>% 
  mutate_ties(tri = tie_is_triangular()) %>% 
  graphr(edge_color = "tri")

ison_adolescents %>% to_directed() %>% 
  mutate_ties(trans = tie_is_transitive()) %>% 
  graphr(edge_color = "trans")

ison_adolescents %>% to_directed() %>% 
  mutate_ties(trip = tie_is_triplet()) %>% 
  graphr(edge_color = "trip")

ison_adolescents %>% to_directed() %>% 
  mutate_ties(cyc = tie_is_cyclical()) %>% 
  graphr(edge_color = "cyc")

ison_monks %>% to_uniplex("like") %>% 
  mutate_ties(simmel = tie_is_simmelian()) %>% 
  graphr(edge_color = "simmel")

generate_random(8, directed = TRUE) %>% 
  mutate_ties(forbid = tie_is_forbidden()) %>% 
  graphr(edge_color = "forbid")

tie_is_imbalanced(ison_marvel_relationships)
#>   `Abomination-Beast` `Abomination-Colossus` `Abomination-Cyclops`
#> 1 TRUE                TRUE                   TRUE                 
#> # ... with 555 more values from this nodeset unprinted. Use `print(..., n = Inf)` to print all values.