bibliometrix (version 1.8)

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", sep = ";")

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 ISI 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 this tags:

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

for a complete list of filed tags see: ISI WoS Field Tags

type

indicates the output format of co-occurrences:

type = "matrix"

produces an object of class matrix

sep

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

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 tranformed into a collection of compatible networks. Through matrix multiplication you can obtain different networks. The fuction follows the approach proposed by Batagely and Cerinsek (2013).

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

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

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

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

# data(scientometrics)

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

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

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

# }