View source: R/dynamic_network_cooccurrence.R
dynamic_network_cooccurrence | R Documentation |
This function was implemented in an earlier version of the development of this package.
It has been replaced by networkflow::build_dynamic_networks()
.
This function creates one or several tidygraph networks from a table of nodes and its
directed edges. For instance, for bibliometric networks, you can give a list of
articles and the list of the references these articles cite. You can use it to
build a single network or multiple networks over different time windows.
dynamic_network_cooccurrence( nodes = NULL, directed_edges = NULL, source_column = NULL, target_column = NULL, time_variable = NULL, time_window = NULL, cooccurrence_method = c("coupling_angle", "coupling_strength", "coupling_similarity"), overlapping_window = FALSE, edges_threshold = 1, compute_size = FALSE, keep_singleton = FALSE, verbose = TRUE )
nodes |
The table with all the nodes and their metadata. For instance, if your nodes are articles, this table is likely to contain the year of publication, the name of the authors, the title of the article, etc... The table must have one row per node. |
directed_edges |
The table with of all the elements to which your nodes are connected. If your nodes are
articles, the |
source_column |
The column with the unique identifier of each node. For instance, for a bibliographic coupling network, the id of your citing documents. |
target_column |
The column with the unique identifier of each element connected to the node (for instance, the identifier of the reference cited by your node if the node is an article). |
time_variable |
The column with the temporal variable you want to use to build your windows for the
succession of networks. By default, |
time_window |
The length of your network relatively of the unity of the |
cooccurrence_method |
Choose a cooccurrence method to build your indirect edges table. The function propose three methods that depends on the biblionetwork package and three methods that are implemented in it:
|
overlapping_window |
Set to |
edges_threshold |
Threshold value for building your edges. With a higher threshold, only the stronger links
will be kept. See the biblionetwork package
documentation and the |
compute_size |
Set to |
keep_singleton |
Set to |
verbose |
Set to |
If time_window
is NULL
, the function computes only
one network and return a tidygraph object built with tbl_graph().
If time_variable
and time_window
are not NULL
, the function returns a list
of tidygraph networks, for each time window.
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 <- dynamic_network_cooccurrence(nodes = nodes, directed_edges = references, source_column = "ID_Art", target_column = "ItemID_Ref", time_variable = "Year", cooccurrence_method = "coupling_similarity", time_window = NULL, edges_threshold = 1, compute_size = FALSE, keep_singleton = FALSE, overlapping_window = TRUE)
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