Given an affiliation network with time-stamped events, compute the proportion of centered triples at which an open wedge exists at some time that is closed at a later time.
dynamic_triad_closure(graph, actors = V(graph)[V(graph)$type == FALSE], type = "global", ..., measure = NULL) dynamic_triad_closure_an(graph, actors = V(graph)[V(graph)$type == FALSE], type = "global", ..., measure = NULL) dynamic_transitivity_an(graph, actors = V(graph)[V(graph)$type == FALSE], type = "global", ..., measure = NULL) dyn.transitivity.an(graph, actors = V(graph)[V(graph)$type == FALSE], type = "global", ..., measure = NULL) dynamic_triad_closure_projection(graph, memory = Inf, type = "global")
graph | An affiliation network with time-stamped events. |
---|---|
actors | A vector of actor nodes in |
type | The type of statistic, matched to |
... | Additional parameters passed to specific functions. |
measure | Character; the measure of triad closure, used as the suffix
|
memory | Numeric; minimum delay of wedge formation since would-have-been closing events. |
Other triad closure functions: project_transitivity
,
transitivity_an
,
triad_closure_from_census
,
triad_closure
data(women_group) dynamic_triad_closure(women_group)#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> [1] 0.5464481cbind( transitivity(actor_projection(women_group), type = "local"), triad_closure_opsahl(women_group, type = "local"), triad_closure_exclusive(women_group, type = "local"), dynamic_triad_closure_projection(women_group, type = "local"), dynamic_triad_closure(women_group, type = "local") )#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> Warning: 'dynamic_wedges' is experimental.#> [,1] [,2] [,3] [,4] [,5] #> [1,] 0.8970588 0.7666667 0.4477612 0.5757576 0.4496124 #> [2,] 0.9619048 0.8421751 0.4871795 0.6923077 0.6052632 #> [3,] 0.8970588 0.7523437 0.1445783 0.6500000 0.5144509 #> [4,] 0.9619048 0.8387909 0.4500000 0.6923077 0.4871795 #> [5,] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 #> [6,] 0.9619048 0.8690476 0.7777778 0.0000000 0.0000000 #> [7,] 0.9619048 0.7959184 0.5312500 0.6923077 0.5652174 #> [8,] 0.9333333 0.6462585 0.4666667 0.6363636 0.4666667 #> [9,] 0.8970588 0.6702509 0.3283582 0.6500000 0.5000000 #> [10,] 0.8970588 0.6740891 0.3928571 0.5757576 0.5185185 #> [11,] 0.9333333 0.7138810 0.5555556 0.2727273 0.4285714 #> [12,] 0.9333333 0.7695560 0.5357143 0.2727273 0.4285714 #> [13,] 0.8970588 0.7461929 0.3000000 0.5757576 0.5714286 #> [14,] 0.8970588 0.8379501 0.6631579 0.7254902 0.7207792 #> [15,] 0.8970588 0.8159204 0.6610169 0.6111111 0.5714286 #> [16,] 0.9333333 0.5407407 0.4666667 0.0000000 0.0000000 #> [17,] 1.0000000 0.5806452 1.0000000 1.0000000 1.0000000 #> [18,] 1.0000000 0.5806452 1.0000000 1.0000000 1.0000000