cocMatrix
computes co-occurences between elements of a Tag Field from a bibliographic data frame. Manuscript is the unit of analysis.
cocMatrix(M, Field = "AU", type = "sparse", sep = ";",
binary = TRUE)
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.
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
indicates the output format of co-occurrences:
type = "matrix" |
produces an object of class
matrix |
is the field separator character. This character separates strings in each
column of the data frame. The default is sep = ";"
.
is a logical. If TRUE each cell contains a 0/1. if FALSE each cell contains the frequency.
a co-occurrence matrix with cases corresponding to manuscripts and variables to the
objects extracted from the Tag Field
.
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.
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.
# 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 = ";")
# }
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