View source: R/networks_to_alluv.R
networks_to_alluv | R Documentation |
This function creates a data.frame that can be easily plotted with ggalluvial from a list of networks.
networks_to_alluv( list_graph = NA, intertemporal_cluster_column = "intertemporal_name", node_id = NA, summary_cl_stats = TRUE, keep_color = TRUE, color_column = "color", keep_cluster_label = TRUE, cluster_label_column = "cluster_label" )
list_graph |
Your list with all networks |
intertemporal_cluster_column |
The column with the identifier of the inter-temporal cluster. If you have used
add_clusters() and merge_dynamic_clusters(),
it is of the form |
node_id |
The column with the unique identifier of each node. |
summary_cl_stats |
If set to
|
keep_color |
Set to |
color_column |
The name of the column with the colors of the categories in |
keep_cluster_label |
Set to |
cluster_label_column |
The name of the column with the name/label associated to the categories in
|
library(networkflow) nodes <- Nodes_stagflation |> dplyr::rename(ID_Art = ItemID_Ref) |> dplyr::filter(Type == "Stagflation") references <- Ref_stagflation |> dplyr::rename(ID_Art = Citing_ItemID_Ref) temporal_networks <- build_dynamic_networks(nodes = nodes, directed_edges = references, source_id = "ID_Art", target_id = "ItemID_Ref", time_variable = "Year", cooccurrence_method = "coupling_similarity", time_window = 20, edges_threshold = 1, overlapping_window = TRUE, filter_components = TRUE, verbose = FALSE) temporal_networks <- add_clusters(temporal_networks, objective_function = "modularity", clustering_method = "leiden", verbose = FALSE) temporal_networks <- merge_dynamic_clusters(temporal_networks, cluster_id = "cluster_leiden", node_id = "ID_Art", threshold_similarity = 0.51, similarity_type = "partial") temporal_networks <- name_clusters(graphs = temporal_networks, method = "tf-idf", name_merged_clusters = TRUE, cluster_id = "dynamic_cluster_leiden", text_columns = "Title", nb_terms_label = 5, clean_word_method = "lemmatise") temporal_networks <- color_networks(graphs = temporal_networks, column_to_color = "dynamic_cluster_leiden", color = NULL) alluv_dt <- networks_to_alluv(temporal_networks, intertemporal_cluster_column = "dynamic_cluster_leiden", node_id = "ID_Art") alluv_dt[1:5]
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