Analyze Cumulative Network Groups Over Time

Performs cumulative community detection on a network over specified time spans, returning group statistics and keyword analysis for each time period.

Usage

sniff_groups_cumulative(
  comps,
  time_span = NULL,
  min_group_size = 10,
  keep_component = c("c1"),
  cluster_component = c("c1"),
  top_n_keywords = 10,
  algorithm = "fast_greedy",
  seed = 888L
)

Arguments

comps

A list containing network components, typically generated by sniff_components(). Must include a network object with 'component' and 'PY' (publication year) vertex attributes.

time_span

Numeric vector of years to analyze (default: 2000:2024).

min_group_size

Minimum size for a cluster to be retained (default = 10).

keep_component

Character vector specifying which network components to process (default = "c1"). Can include multiple components.

cluster_component

Character vector specifying which components should be clustered (default = "c1"). Components not listed here will be treated as single groups.

top_n_keywords

Number of top keywords to extract per group (default = 10).

algorithm

Community detection algorithm to use. One of: "louvain", "walktrap", "edge_betweenness", "fast_greedy" (default), or "leiden".

seed

Random seed for reproducible results (default = 888L). Only applies to algorithms that use random initialization like Louvain.

Value

A named list (by year) where each element contains:

groups

A tibble with group statistics and top keywords

documents

A tibble mapping documents to groups

network

The cumulative network up to that year

Examples

if (FALSE) { # \dontrun{
# Typical pipeline:
data <- read_wos("savedrecs.txt")
net <- sniff_network(data)
comps <- sniff_components(net)

# Cumulative analysis
groups_cumulative <- sniff_groups_cumulative(
  comps,
  time_span = 2010:2020,
  keep_component = c("c1", "c2"),
  cluster_component = c("c1"),
  algorithm = "leiden",
  seed = 888L
)

# Access results for 2015
groups_cumulative[["network_until_2015"]]$groups
} # }