Enhanced Segment Membership with Meaningful Names

Returns segment membership information with an additional column containing meaningful segment names derived from the constituent nodes. This function extends segment.membership by adding intelligent naming strategies for aggregated segments.

Usage

segment.membership.enhanced(
  segments,
  level = seq(segments$segment.list),
  naming_strategy = "auto",
  custom_names = NULL,
  separator = " + ",
  max_concat_length = 2,
  pattern_rules = NULL
)

Arguments

segments

A moneca object returned by moneca.

level

Integer vector specifying which hierarchical levels to include. Default includes all available levels.

naming_strategy

Character string specifying the naming approach:

• "auto" (default): Automatic naming based on segment composition

• "concat": Concatenate node names with separator

• "pattern": Use pattern recognition for common suffixes/prefixes

• "custom": Use user-provided names from custom_names parameter

custom_names

Named list providing custom names for specific segments. Format: list("level.segment" = "Custom Name"), e.g., list("2.1" = "Blue Collar")

separator

Character string used to separate names when concatenating. Default is " + ".

max_concat_length

Maximum number of names to concatenate before switching to pattern-based naming. Default is 2.

pattern_rules

Enhanced pattern rules list with priorities and semantic categories. Default includes comprehensive occupational and industry patterns (avoiding generic social class terms).

Value

A data frame with three columns:

name

Character vector of original category names

membership

Character vector indicating segment membership, formatted as "level.segment" (e.g., "2.1" for level 2, segment 1)

segment_label

Character vector with meaningful segment names derived from constituent nodes or user-provided names

Details

The function applies different naming strategies based on segment composition:

1. Individual nodes: Keep original name unchanged

2. Small segments (<= max_concat_length): Concatenate names

3. Large segments: Apply pattern recognition or use generic names

4. Custom names: Override automatic naming with user-provided names

The enhanced pattern recognition system uses weighted scoring to identify occupational hierarchies, industry sectors, and employment types. It creates semantically meaningful names like "Executive_Leadership", "Professional_Services", or "Technical_Specialists" based on segment composition, avoiding generic terms.

See also

segment.membership for basic membership information, moneca for the main analysis function

Examples

if (FALSE) { # \dontrun{
# Generate data and run analysis
mob_data <- generate_mobility_data(n_classes = 6, seed = 42)
seg <- moneca(mob_data, segment.levels = 3)

# Get enhanced membership with automatic naming
enhanced <- segment.membership.enhanced(seg)
print(enhanced)
} # }