Find conversations by unit — tma.conversations • tma

Identify and extract rows corresponding to conversations for specified units in a dataset or context model. Useful for subsetting and analyzing conversational windows in network analysis.

Usage

tma.conversations(
  x,
  units,
  units.by = NULL,
  codes = NULL,
  conversation.by = NULL,
  window = 4,
  conversation.exclude = c(),
  id_col = "QEUNIT"
)

Arguments

x: A data.frame or context model containing conversation data.
units: Character vector of unit identifiers to extract conversations for.
units.by: Character vector of column names specifying unit grouping (default: from context model attributes).
codes: Character vector of code columns to use for identifying coded rows.
conversation.by: Character vector of column names to group by conversation.
window: Integer; window size for co-occurrence (default: 4).
conversation.exclude: Character vector of conversation keys to exclude.
id_col: Character; column name for unit IDs (default: "QEUNIT").

Value

A list with elements:

conversations: List of row indices for each conversation.
unitConvs: Unique conversation keys for the specified units.
allRows: All row indices included for the units.
unitRows: Row indices for the units with codes.
convRows: All row indices for the unit's conversations.
toRemove: Rows not meeting co-occurrence criteria.

Details

This function groups rows by conversation (using `conversation.by` columns), identifies which rows are associated with the specified units and codes, and returns indices for each conversation, as well as metadata about which rows to include or exclude.