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.
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.
Examples
if (FALSE) { # \dontrun{
# Load example data
data(icews)
# Create a simple network
ntwk <- netify(
icews,
actor1 = "i", actor2 = "j",
time = "year",
symmetric = FALSE,
weight = "matlCoop"
)
# Run homophily analysis
homophily_result <- homophily(
ntwk,
attribute = "i_polity2",
method = "correlation"
)
# Create distribution plot
plot_homophily(
homophily_result,
netlet = ntwk,
type = "distribution",
attribute = "i_polity2"
)
} # }