cocMatrix function

Bibliographic bipartite network matrices

cocMatrix computes occurrences between elements of a Tag Field from a bibliographic data frame. Manuscript is the unit of analysis.

cocMatrix(
  M,
  Field = "AU",
  type = "sparse",
  n = NULL,
  sep = ";",
  binary = TRUE,
  short = FALSE,
  remove.terms = NULL,
  synonyms = NULL
)

Arguments

• M: is a data frame obtained by the converting function convert2df. It is a data matrix with cases corresponding to articles and variables to Field Tag in the original WoS or SCOPUS file.

• Field: is a character object. It indicates one of the field tags of the standard ISI WoS Field Tag codify. Field can be equal to one of these tags:

  AU		Authors
  SO		Publication Name (or Source)
  JI		ISO Source Abbreviation
  DE		Author Keywords
  ID		Keywords associated by WoS or SCOPUS database
  CR		Cited References

  for a complete list of filed tags see: Field Tags used in bibliometrix

• type: indicates the output format of co-occurrences:

  type = "matrix"		produces an object of class matrix
  type = "sparse"		produces an object of class dgMatrix of the package Matrix . "sparse" argument generates a compact representation of the matrix.

• n: is an integer. It indicates the number of items to select. If N = NULL, all items are selected.

• sep: is the field separator character. This character separates strings in each column of the data frame. The default is sep = ";".

• binary: is a logical. If TRUE each cell contains a 0/1. if FALSE each cell contains the frequency.

• short: is a logical. If TRUE all items with frequency<2 are deleted to reduce the matrix size.

• remove.terms: is a character vector. It contains a list of additional terms to delete from the documents before term extraction. The default is remove.terms = NULL.

• synonyms: is a character vector. Each element contains a list of synonyms, separated by ";", that will be merged into a single term (the first word contained in the vector element). The default is synonyms = NULL.

Returns

a bipartite network matrix with cases corresponding to manuscripts and variables to the objects extracted from the Tag Field.

Details

This occurrence matrix represents a bipartite network which can be transformed into a collection of bibliographic networks such as coupling, co-citation, etc..

The function follows the approach proposed by Batagelj & Cerinsek (2013) and Aria & cuccurullo (2017).

References:

Batagelj, V., & Cerinsek, M. (2013). On bibliographic networks. Scientometrics, 96(3), 845-864.

Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975.

Examples

# EXAMPLE 1: Articles x Authors occurrence matrix

data(scientometrics, package = "bibliometrixData")
WA <- cocMatrix(scientometrics, Field = "AU", type = "sparse", sep = ";")

# EXAMPLE 2: Articles x Cited References occurrence matrix

# data(scientometrics, package = "bibliometrixData")

# WCR <- cocMatrix(scientometrics, Field = "CR", type = "sparse", sep = ";")

# EXAMPLE 3: Articles x Cited First Authors occurrence matrix

# data(scientometrics, package = "bibliometrixData")
# scientometrics <- metaTagExtraction(scientometrics, Field = "CR_AU", sep = ";")
# WCR <- cocMatrix(scientometrics, Field = "CR_AU", type = "sparse", sep = ";")

See Also

convert2df to import and convert an ISI or SCOPUS Export file in a data frame.

biblioAnalysis to perform a bibliometric analysis.

biblioNetwork to compute a bibliographic network.