Visualize homophily analysis results

creates visualizations for homophily analysis results from homophily(). the function can create different types of plots including similarity distributions, comparison plots across multiple attributes, and temporal evolution plots.

Usage

plot_homophily(
  homophily_results,
  netlet = NULL,
  type = c("distribution", "comparison", "temporal"),
  attribute = NULL,
  method = "correlation",
  sample_size = NULL,
  colors = c("#2E86AB", "#F18F01"),
  ...
)

Arguments

homophily_results

data frame output from homophily() or a list of such data frames for comparison plots.

netlet

optional. the netify object used in the analysis. required for distribution plots to extract actual similarity data.

type

character string specifying the plot type:

"distribution"

shows similarity score distributions for connected vs unconnected pairs (requires netlet)

"comparison"

compares homophily across multiple attributes

"temporal"

shows homophily evolution over time (for longitudinal data)

attribute

character string. for distribution plots, specifies which attribute to visualize. should match the attribute used in homophily().

method

character string. for distribution plots, the similarity method used. should match the method used in homophily().

sample_size

integer. for distribution plots with large networks, the number of dyad pairs to sample for visualization. default is NULL (use all pairs).

colors

character vector of two colors for connected/unconnected or significant/non-significant pairs. default uses package theme colors.

...

additional arguments passed to ggplot2 functions.

Value

a ggplot2 object that can be further customized.

Author

cassy dorff, shahryar minhas

Examples

# \donttest{
# load example data
data(classroom_edges)
data(classroom_nodes)

# create a network with nodal attributes
ntwk <- netify(
    classroom_edges,
    actor1 = "from", actor2 = "to",
    symmetric = TRUE,
    nodal_data = classroom_nodes
)

# run homophily analysis
homophily_result <- homophily(
    ntwk,
    attribute = "gender",
    method = "categorical",
    n_permutations = 100
)

# create distribution plot
plot_homophily(
    homophily_result,
    netlet = ntwk,
    type = "distribution",
    attribute = "gender",
    method = "categorical"
)
#> ℹ Similarity matrix: 30x30
#> ℹ Binary network: 30x30
#> ℹ Similarity keys: 870, Binary keys: 870
#> ℹ Matched: 870, Unmatched: 0
#> ℹ Similarity data dimensions: 870 rows x 2 cols
#> ℹ Connected levels: Connected, Not Connected
#> ℹ Connected counts: Connected=102, Not Connected=768

# }