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This function analyzes the evolution of document groups over time to detect technological trajectories and scientific emergence patterns. It computes similarity measures between groups across time periods and tracks their attributes.

Usage

sniff_groups_trajectories(
  groups_cumulative,
  min_group_size = 10,
  top_n_keywords = 3
)

Arguments

groups_cumulative

A list of cumulative group data over time, typically produced by other functions in the birddog package. Each element should contain network, documents, and groups data.

min_group_size

Minimum number of documents required for a group to be considered (default: 10). Smaller groups will be filtered out.

top_n_keywords

Number of top keywords to consider when analyzing group characteristics (default: 3).

Value

A list with two components:

  • groups_attributes: A list of data frames containing attributes for each tracked group

  • groups_similarity: A list of data frames containing Jaccard similarity measures between groups across time periods

Examples

if (FALSE) { # \dontrun{
# Assuming you have cumulative group data:
trajectories <- sniff_groups_trajectories(groups_cumulative, min_group_size = 15)
} # }