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Create a netify array from longitudinal dyadic data

Source: R/get_adjacency_array.R
get_adjacency_array.Rd

get_adjacency_array converts longitudinal dyadic data into a three-dimensional netify array where the first two dimensions represent actors and the third dimension represents time periods. This function creates an array of class "netify" and should only be used when actor composition remains constant across all time periods.

Usage

get_adjacency_array(
  dyad_data,
  actor1 = NULL,
  actor2 = NULL,
  time = NULL,
  symmetric = TRUE,
  mode = "unipartite",
  weight = NULL,
  sum_dyads = FALSE,
  diag_to_NA = TRUE,
  missing_to_zero = TRUE
)

Arguments

dyad_data

A data.frame containing longitudinal dyadic observations. Will be coerced to data.frame if a tibble or data.table is provided.

actor1

Character string specifying the column name for the first actor in each dyad.

actor2

Character string specifying the column name for the second actor in each dyad.

time

Character string specifying the column name for time periods.

symmetric

Logical. If TRUE (default), treats the network as undirected (i.e., edges have no direction). If FALSE, treats the network as directed.

mode

Character string specifying network structure. Options are:

  • "unipartite": One set of actors (default)

  • "bipartite": Two distinct sets of actors

weight

Character string specifying the column name containing edge weights. If NULL (default), edges are treated as unweighted (binary).

sum_dyads

Logical. If TRUE, sums weight values when multiple edges exist between the same actor pair in the same time period. If FALSE (default), uses the last observed value.

diag_to_NA

Logical. If TRUE (default), sets diagonal values (self-loops) to NA. Automatically set to FALSE for bipartite networks.

missing_to_zero

Logical. If TRUE (default), treats missing edges as zeros. If FALSE, missing edges remain as NA.

Value

A three-dimensional array of class "netify" (a netify array) with:

  • Dimensions: [n_actors × n_actors × n_time] for unipartite networks or [n_actors1 × n_actors2 × n_time] for bipartite networks

  • Class: "netify" - this is a full netify object compatible with all netify functions

  • Attributes: Extensive metadata including network properties, actor information, and processing parameters

The returned object is a netify array that can be used with all netify functions such as summary(), plot(), to_igraph(), etc.

Details

Note on usage:

While this function is exported and available for direct use, the primary and recommended way to create netify arrays from longitudinal dyadic data is through the netify() function. The netify() function:

  • Automatically determines whether to create an array or list structure

  • Handles time-varying actor composition

  • Provides more comprehensive data validation

  • Offers a unified interface for all types of network data

Use get_adjacency_array() directly only when you specifically need low-level control over array creation and are certain your actors remain constant across time.

Author

Cassy Dorff, Ha Eun Choi, Shahryar Minhas

Examples

# Load example data
data(icews)

# Create a netify array (longitudinal directed network)
# with material conflict as edge weights
icews_array <- get_adjacency_array(
  dyad_data = icews, 
  actor1 = 'i', 
  actor2 = 'j', 
  time = 'year',
  symmetric = FALSE, 
  weight = 'matlConf'
)

# Verify it's a netify object
class(icews_array)  # "netify"
#> [1] "netify"

# Check dimensions
dim(icews_array)  # [n_actors, n_actors, n_years]
#> [1] 152 152  13

# Access specific time period
icews_2010 <- icews_array[,,"2010"]