Build a document network

Constructs a network between documents (papers) in the dataset.

Usage

document_network(
  data,
  type = "coupling",
  counting = "full",
  similarity = "none",
  threshold = 0,
  min_occur = 1L,
  top_n = NULL,
  self_loops = FALSE,
  deduplicate = TRUE,
  format = "edgelist",
  references = "references",
  sep = ";",
  strip_quotes = TRUE,
  id = NULL
)

Arguments

data

A data frame with id and a references column (list-column or delimited string).

type

Character. Relationship type:

"coupling"

Bibliographic coupling: documents linked when they share cited references.

"citation"

Direct citation: directed edges from citing to cited documents (internal citations only).

"co_citation"

Co-citation: documents linked when they are cited together by other documents in the dataset.

"equivalence"

Profile similarity of reference vectors.

counting

Character. Counting method. Default "full". Position-dependent methods are not applicable to document networks.

similarity

Character. Similarity measure. Default "none".

threshold

Numeric. Minimum edge weight. Default 0.

min_occur

Integer. Minimum reference frequency. Default 1.

top_n

Integer or NULL. Return only the top n edges by weight. Default NULL (all edges).

self_loops

Logical. If TRUE, include self-loops (an entity linked to itself). Default FALSE.

deduplicate

Logical. If TRUE (default), each (paper, entity) pair is counted at most once — duplicate entries in the source data (e.g., the same author listed twice on a paper) are treated as one occurrence. Set to FALSE to count every raw occurrence.

format

Character. Output format:

"edgelist"

Default. A bibnets_network data frame with columns from, to, weight, count.

"gephi"

Gephi-ready data frame: Source, Target, Weight, Count, Type.

"igraph"

An igraph graph object (requires igraph).

"cograph"

A cograph_network object (requires cograph).

"matrix"

A sparse adjacency matrix.

references

Character. Name of the column containing cited references. Default "references".

sep

Character. Separator used to split the entity column when it is a plain character column rather than a list-column, e.g. sep = "," or sep = " and ". Default ";". Ignored for list-columns. sep applies only to the author column; the references column uses references_sep.

strip_quotes

Logical. If TRUE (default), surrounding quote characters are removed from each reference.

id

Optional. Name of the column to use as the work identifier (the matrix-row dimension). If NULL (default), an existing id column is used when present, otherwise row numbers are used.

Value

Depends on format. For type = "citation", edges are directed (from = citing, to = cited) with weight and count both 1.

Examples

data(biblio_data)
document_network(biblio_data, "coupling")
#> # bibnets network: document_coupling | 10 nodes · 36 edges | counting: full 
#>     from  to  weight  count
#>  1  W4    W9       4      4
#>  2  W1    W3       3      3
#>  3  W4    W6       3      3
#>  4  W1    W7       3      3
#>  5  W6    W9       3      3
#>  6  W1    W2       2      2
#>  7  W2    W3       2      2
#>  8  W2    W4       2      2
#>  9  W3    W4       2      2
#> 10  W2    W5       2      2
#> # ... 26 more edges
document_network(biblio_data, "coupling", counting = "strength")
#> # bibnets network: document_coupling | 10 nodes · 36 edges | counting: strength 
#>     from  to   weight  count
#>  1  W4    W9   0.1981      4
#>  2  W1    W7   0.1938      3
#>  3  W1    W3   0.1619      3
#>  4  W6    W10  0.1579      2
#>  5  W4    W6   0.1229      3
#>  6  W5    W8   0.1229      2
#>  7  W6    W9   0.1229      3
#>  8  W1    W2   0.1186      2
#>  9  W2    W7   0.1186      2
#> 10  W3    W7   0.1186      2
#> # ... 26 more edges