cocMatrix {bibliometrix}R Documentation

Bibliographic bipartite network matrices

Description

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

Usage

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.

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.

Value

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

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.

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 = ";")


[Package bibliometrix version 4.1.4 Index]