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bibliometrix (version 3.1.4)

cocMatrix: Co-occurrence matrix

Description

cocMatrix computes co-occurences 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
)

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

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
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.

Value

a co-occurrence matrix with cases corresponding to manuscripts and variables to the objects extracted from the Tag Field.

Details

This co-occurrence matrix can be transformed into a collection of compatible networks. Through matrix multiplication you can obtain different networks. 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.

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

Run this code
# NOT RUN {
# EXAMPLE 1: Articles x Authors co-occurrence matrix

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

# EXAMPLE 2: Articles x Cited References co-occurrence matrix

# data(scientometrics, package = "bibliometrixData")

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

# EXAMPLE 3: Articles x Cited First Authors co-occurrence matrix

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

# }

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