Nothing

```
# Subgraphs and Modularity
# discourseGT
# MIT License
# Documentation
#' Runs subgroup analysis on graphs
#'
#' Performs a subgroup analysis on the graph
#'
#' @param ginp The prepared graph object from prepareGraphs function
#' @param raw_input The data of the original .csv file
#' @param normalized Normalize the betweeness centrality values
#'
#' @return Saves number of potential cliques, cores, symmetry of the graph, dyads in graphs, node composition in proposed cliques, neighbors adjacent to each node, transitivity (local and global) as a list object
#'
#' @examples
#' df <- sampleData1
#' prepNet <- tabulate_edges(df, iscsvfile = FALSE, silentNodes = 0)
#' baseNet <- prepareGraphs(prepNet, project_title = "Sample Data 1", weightedGraph = TRUE)
#' subgroupsNetAnalysis(baseNet, raw_input = df)
#'
subgroupsNetAnalysis <- function(ginp, raw_input = NULL, normalized = FALSE){
# Creates the object as undirected for this function only
g <- igraph::graph_from_adjacency_matrix(ginp$graphmatrix, mode = "undirected")
# Determine subgroups with the Girvan-Newman algorithm
tabEdgeTemp <- tabulate_edges(input = raw_input, iscsvfile = FALSE)
prepGraphsDirTemp <- prepareGraphs(raw_data_input = tabEdgeTemp)
g_sub <- suppressWarnings(igraph::cluster_edge_betweenness(prepGraphsDirTemp$graph))
# Report the betweenness values
g_bet <- igraph::betweenness(graph = ginp$graph, directed = TRUE, normalized = normalized)
# Does loop function for each group to output members list
# Function is under Summary of Variables for Analysis because of print function required
# Determines core membranes of the group
cores <- igraph::graph.coreness(ginp$graph)
# Determines symmetry of the group
# Calls the directed version of the graph
gdir <- ginp$graph
# Generates simplified data of graph with no loops or multiple edges
graph_symet_pre <- igraph::simplify(gdir)
# Creates list of census of how symmetric the graph is
graph_symet <- igraph::dyad.census(graph_symet_pre)
# Graph Connectedness Census
g_comps <- igraph::decompose.graph(ginp$graph)
g_comps_table <- table(sapply(g_comps, igraph::vcount))
# Generates a list the neighborhood of each of the nodes adjacent to one another
neigh_g <- igraph::neighborhood(ginp$graph)
# Transitivity/Clustering Coefficients
# Measures the probability that the adjacent vertices of a vertex are connected
#(Based on the number of triangles connected to vertex and triplets centered around vertex)
# Transitivity of Local values
g_trans_local <- igraph::transitivity(ginp$graph, type = "local")
# Transitivity of Global values
g_trans_global <- igraph::transitivity(ginp$graph, type = "global")
objectsReturned <- list(g_sub = g_sub,
normalized = normalized,
g_bet = g_bet,
cores = cores,
graph_symet = graph_symet_pre,
dyad_graph_symet = graph_symet,
g_comps = g_comps,
g_comps_table = g_comps_table,
neighborsList = neigh_g,
transitivity_local = g_trans_local,
transitivity_global = g_trans_global)
return(objectsReturned)
}
```

**Any scripts or data that you put into this service are public.**

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.