couplingMap {bibliometrix}R Documentation

Coupling Analysis

Description

It performs a coupling network analysis and plots community detection results on a bi-dimensional map (Coupling Map).

Usage

couplingMap(
  M,
  analysis = "documents",
  field = "CR",
  n = 500,
  label.term = NULL,
  ngrams = 1,
  impact.measure = "local",
  minfreq = 5,
  stemming = FALSE,
  size = 0.5,
  n.labels = 1,
  repel = TRUE
)

Arguments

M

is a bibliographic dataframe.

analysis

is the textual attribute used to select the unit of analysis. It can be analysis = c("documents", "authors", "sources").

field

is the textual attribute used to measure the coupling strength. It can be field = c("CR", "ID","DE", "TI", "AB").

n

is an integer. It indicates the number of units to include in the analysis.

label.term

is a character. It indicates which content metadata have to use for cluster labeling. It can be label.term = c("ID","DE","TI","AB"). If label.term = NULL cluster items will be use for labeling.

ngrams

is an integer between 1 and 4. It indicates the type of n-gram to extract from texts. An n-gram is a contiguous sequence of n terms. The function can extract n-grams composed by 1, 2, 3 or 4 terms. Default value is ngrams=1.

impact.measure

is a character. It indicates the impact measure used to rank cluster elements (documents, authors or sources). It can be impact.measure = c("local", "global").\ With impact.measure = "local", couplingMap calculates elements impact using the Normalized Local Citation Score while using codeimpact.measure = "global", the function uses the Normalized Global Citation Score to measure elements impact.

minfreq

is a integer. It indicates the minimum frequency (per thousand) of a cluster. It is a number in the range (0,1000).

stemming

is logical. If it is TRUE the word (from titles or abstracts) will be stemmed (using the Porter's algorithm).

size

is numerical. It indicates the size of the cluster circles and is a number in the range (0.01,1).

n.labels

is integer. It indicates how many labels associate to each cluster. Default is n.labels = 1.

repel

is logical. If it is TRUE ggplot uses geom_label_repel instead of geom_label.

Details

The analysis can be performed on three different units: documents, authors or sources and the coupling strength can be measured using the classical approach (coupled by references) or a novel approach based on unit contents (keywords or terms from titles and abstracts)

The x-axis measures the cluster centrality (by Callon's Centrality index) while the y-axis measures the cluster impact by Mean Normalized Local Citation Score (MNLCS). The Normalized Local Citation Score (NLCS) of a document is calculated by dividing the actual count of local citing items by the expected citation rate for documents with the same year of publication.

Value

a list containing:

map The coupling map as ggplot2 object
clusters Centrality and Density values for each cluster.
data A list of units following in each cluster
nclust The number of clusters
NCS The Normalized Citation Score dataframe
net A list containing the network output (as provided from the networkPlot function)

See Also

biblioNetwork function to compute a bibliographic network.

cocMatrix to compute a bibliographic bipartite network.

networkPlot to plot a bibliographic network.

Examples


## Not run: 
data(management, package = "bibliometrixData")
res <- couplingMap(management, analysis = "authors", field = "CR", n = 250, impact.measure="local", 
                   minfreq = 3, size = 0.5, repel = TRUE)
plot(res$map)

## End(Not run)


[Package bibliometrix version 3.1.4 Index]